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- .gitattributes +1 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/__init__.py +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/__pycache__/__init__.cpython-310.pyc +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/__init__.py +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/__pycache__/__init__.cpython-310.pyc +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublas.h +891 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublasLt.h +1815 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublasXt.h +693 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublas_api.h +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublas_v2.h +478 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/nvblas.h +824 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/lib/__init__.py +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/lib/__pycache__/__init__.cpython-310.pyc +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cublas/lib/libnvblas.so.12 +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/__pycache__/__init__.cpython-310.pyc +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/__pycache__/__init__.cpython-310.pyc +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/builtin_types.h +64 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/common_functions.h +65 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/async.h +452 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/coalesced_reduce.h +108 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/coalesced_scan.h +174 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/driver_abi.h +99 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/functional.h +212 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/helpers.h +634 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/info.h +338 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/invoke.h +189 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/memory.h +135 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/partitioning.h +133 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/reduce.h +429 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/scan.h +320 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/sync.h +267 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/memcpy_async.h +62 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/reduce.h +63 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/scan.h +63 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudaVDPAU.h +282 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_awbarrier.h +280 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_fp8.hpp +1546 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_gl_interop.h +514 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_vdpau_interop.h +201 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_double_functions.h +65 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_types.h +81 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/driver_types.h +0 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/host_config.h +65 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/library_types.h +103 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/math_constants.h +152 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_atomic_functions.h +141 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_intrinsics.hpp +588 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/surface_functions.h +124 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/texture_indirect_functions.h +638 -0
- env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/texture_types.h +177 -0
.gitattributes
CHANGED
@@ -140,3 +140,4 @@ env-llmeval/lib/python3.10/site-packages/nvidia/cudnn/lib/libcudnn_ops_train.so.
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env-llmeval/lib/python3.10/site-packages/nvidia/nvjitlink/lib/libnvJitLink.so.12 filter=lfs diff=lfs merge=lfs -text
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env-llmeval/lib/python3.10/site-packages/nvidia/cudnn/lib/libcudnn_cnn_train.so.8 filter=lfs diff=lfs merge=lfs -text
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env-llmeval/lib/python3.10/site-packages/nvidia/nvjitlink/lib/libnvJitLink.so.12 filter=lfs diff=lfs merge=lfs -text
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env-llmeval/lib/python3.10/site-packages/nvidia/cudnn/lib/libcudnn_adv_train.so.8 filter=lfs diff=lfs merge=lfs -text
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env-llmeval/lib/python3.10/site-packages/nvidia/cufft/lib/libcufftw.so.11 filter=lfs diff=lfs merge=lfs -text
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env-llmeval/lib/python3.10/site-packages/nvidia/cublas/__init__.py
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env-llmeval/lib/python3.10/site-packages/nvidia/cublas/__pycache__/__init__.cpython-310.pyc
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/*
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* Copyright 1993-2019 NVIDIA Corporation. All rights reserved.
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*
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* NOTICE TO LICENSEE:
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*
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* This source code and/or documentation ("Licensed Deliverables") are
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* subject to NVIDIA intellectual property rights under U.S. and
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* international Copyright laws.
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*
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* These Licensed Deliverables contained herein is PROPRIETARY and
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* CONFIDENTIAL to NVIDIA and is being provided under the terms and
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* conditions of a form of NVIDIA software license agreement by and
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* between NVIDIA and Licensee ("License Agreement") or electronically
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* accepted by Licensee. Notwithstanding any terms or conditions to
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* the contrary in the License Agreement, reproduction or disclosure
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* of the Licensed Deliverables to any third party without the express
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* written consent of NVIDIA is prohibited.
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*
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* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
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* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
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* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
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* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
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* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
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* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
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* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
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* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
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* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
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* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
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* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
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* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
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* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
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* OF THESE LICENSED DELIVERABLES.
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*
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* U.S. Government End Users. These Licensed Deliverables are a
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* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
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* 1995), consisting of "commercial computer software" and "commercial
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* computer software documentation" as such terms are used in 48
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* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
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* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
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* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
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* U.S. Government End Users acquire the Licensed Deliverables with
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* only those rights set forth herein.
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*
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* Any use of the Licensed Deliverables in individual and commercial
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* software must include, in the user documentation and internal
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* comments to the code, the above Disclaimer and U.S. Government End
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* Users Notice.
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*/
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/*
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* This is the public header file for the CUBLAS library, defining the API
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*
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* CUBLAS is an implementation of BLAS (Basic Linear Algebra Subroutines)
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* on top of the CUDA runtime.
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*/
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#if !defined(CUBLAS_H_)
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#define CUBLAS_H_
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#if defined(CUBLAS_V2_H_)
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#error "It is an error to include both cublas.h and cublas_v2.h"
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#endif
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#include <cuda_runtime.h>
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#ifndef CUBLASWINAPI
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#ifdef _WIN32
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#define CUBLASWINAPI __stdcall
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#else
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#define CUBLASWINAPI
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#endif
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#endif
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#undef CUBLASAPI
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#ifdef __CUDACC__
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#define CUBLASAPI __host__
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#else
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#define CUBLASAPI
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#endif
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#include "cublas_api.h"
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#if defined(__cplusplus)
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extern "C" {
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#endif
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/* CUBLAS data types */
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#define cublasStatus cublasStatus_t
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cublasStatus CUBLASWINAPI cublasInit(void);
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cublasStatus CUBLASWINAPI cublasShutdown(void);
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cublasStatus CUBLASWINAPI cublasGetError(void);
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cublasStatus CUBLASWINAPI cublasGetVersion(int* version);
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cublasStatus CUBLASWINAPI cublasAlloc(int n, int elemSize, void** devicePtr);
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cublasStatus CUBLASWINAPI cublasFree(void* devicePtr);
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cublasStatus CUBLASWINAPI cublasSetKernelStream(cudaStream_t stream);
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/* ---------------- CUBLAS BLAS1 functions ---------------- */
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/* NRM2 */
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float CUBLASWINAPI cublasSnrm2(int n, const float* x, int incx);
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double CUBLASWINAPI cublasDnrm2(int n, const double* x, int incx);
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float CUBLASWINAPI cublasScnrm2(int n, const cuComplex* x, int incx);
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double CUBLASWINAPI cublasDznrm2(int n, const cuDoubleComplex* x, int incx);
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/*------------------------------------------------------------------------*/
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/* DOT */
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float CUBLASWINAPI cublasSdot(int n, const float* x, int incx, const float* y, int incy);
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double CUBLASWINAPI cublasDdot(int n, const double* x, int incx, const double* y, int incy);
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cuComplex CUBLASWINAPI cublasCdotu(int n, const cuComplex* x, int incx, const cuComplex* y, int incy);
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cuComplex CUBLASWINAPI cublasCdotc(int n, const cuComplex* x, int incx, const cuComplex* y, int incy);
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cuDoubleComplex CUBLASWINAPI cublasZdotu(int n, const cuDoubleComplex* x, int incx, const cuDoubleComplex* y, int incy);
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cuDoubleComplex CUBLASWINAPI cublasZdotc(int n, const cuDoubleComplex* x, int incx, const cuDoubleComplex* y, int incy);
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/*------------------------------------------------------------------------*/
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/* SCAL */
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void CUBLASWINAPI cublasSscal(int n, float alpha, float* x, int incx);
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void CUBLASWINAPI cublasDscal(int n, double alpha, double* x, int incx);
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void CUBLASWINAPI cublasCscal(int n, cuComplex alpha, cuComplex* x, int incx);
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void CUBLASWINAPI cublasZscal(int n, cuDoubleComplex alpha, cuDoubleComplex* x, int incx);
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void CUBLASWINAPI cublasCsscal(int n, float alpha, cuComplex* x, int incx);
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void CUBLASWINAPI cublasZdscal(int n, double alpha, cuDoubleComplex* x, int incx);
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/*------------------------------------------------------------------------*/
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/* AXPY */
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void CUBLASWINAPI cublasSaxpy(int n, float alpha, const float* x, int incx, float* y, int incy);
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void CUBLASWINAPI cublasDaxpy(int n, double alpha, const double* x, int incx, double* y, int incy);
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void CUBLASWINAPI cublasCaxpy(int n, cuComplex alpha, const cuComplex* x, int incx, cuComplex* y, int incy);
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void CUBLASWINAPI
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cublasZaxpy(int n, cuDoubleComplex alpha, const cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy);
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/*------------------------------------------------------------------------*/
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/* COPY */
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void CUBLASWINAPI cublasScopy(int n, const float* x, int incx, float* y, int incy);
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void CUBLASWINAPI cublasDcopy(int n, const double* x, int incx, double* y, int incy);
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void CUBLASWINAPI cublasCcopy(int n, const cuComplex* x, int incx, cuComplex* y, int incy);
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void CUBLASWINAPI cublasZcopy(int n, const cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy);
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/*------------------------------------------------------------------------*/
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/* SWAP */
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void CUBLASWINAPI cublasSswap(int n, float* x, int incx, float* y, int incy);
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void CUBLASWINAPI cublasDswap(int n, double* x, int incx, double* y, int incy);
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void CUBLASWINAPI cublasCswap(int n, cuComplex* x, int incx, cuComplex* y, int incy);
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void CUBLASWINAPI cublasZswap(int n, cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy);
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/*------------------------------------------------------------------------*/
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/* AMAX */
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int CUBLASWINAPI cublasIsamax(int n, const float* x, int incx);
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int CUBLASWINAPI cublasIdamax(int n, const double* x, int incx);
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int CUBLASWINAPI cublasIcamax(int n, const cuComplex* x, int incx);
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int CUBLASWINAPI cublasIzamax(int n, const cuDoubleComplex* x, int incx);
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/*------------------------------------------------------------------------*/
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/* AMIN */
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int CUBLASWINAPI cublasIsamin(int n, const float* x, int incx);
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int CUBLASWINAPI cublasIdamin(int n, const double* x, int incx);
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+
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int CUBLASWINAPI cublasIcamin(int n, const cuComplex* x, int incx);
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int CUBLASWINAPI cublasIzamin(int n, const cuDoubleComplex* x, int incx);
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/*------------------------------------------------------------------------*/
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/* ASUM */
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float CUBLASWINAPI cublasSasum(int n, const float* x, int incx);
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double CUBLASWINAPI cublasDasum(int n, const double* x, int incx);
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float CUBLASWINAPI cublasScasum(int n, const cuComplex* x, int incx);
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double CUBLASWINAPI cublasDzasum(int n, const cuDoubleComplex* x, int incx);
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/*------------------------------------------------------------------------*/
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/* ROT */
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void CUBLASWINAPI cublasSrot(int n, float* x, int incx, float* y, int incy, float sc, float ss);
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void CUBLASWINAPI cublasDrot(int n, double* x, int incx, double* y, int incy, double sc, double ss);
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void CUBLASWINAPI cublasCrot(int n, cuComplex* x, int incx, cuComplex* y, int incy, float c, cuComplex s);
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void CUBLASWINAPI
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cublasZrot(int n, cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy, double sc, cuDoubleComplex cs);
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void CUBLASWINAPI cublasCsrot(int n, cuComplex* x, int incx, cuComplex* y, int incy, float c, float s);
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void CUBLASWINAPI cublasZdrot(int n, cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy, double c, double s);
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/*------------------------------------------------------------------------*/
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/* ROTG */
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void CUBLASWINAPI cublasSrotg(float* sa, float* sb, float* sc, float* ss);
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void CUBLASWINAPI cublasDrotg(double* sa, double* sb, double* sc, double* ss);
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void CUBLASWINAPI cublasCrotg(cuComplex* ca, cuComplex cb, float* sc, cuComplex* cs);
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void CUBLASWINAPI cublasZrotg(cuDoubleComplex* ca, cuDoubleComplex cb, double* sc, cuDoubleComplex* cs);
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/*------------------------------------------------------------------------*/
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/* ROTM */
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void CUBLASWINAPI cublasSrotm(int n, float* x, int incx, float* y, int incy, const float* sparam);
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void CUBLASWINAPI cublasDrotm(int n, double* x, int incx, double* y, int incy, const double* sparam);
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/*------------------------------------------------------------------------*/
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/* ROTMG */
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void CUBLASWINAPI cublasSrotmg(float* sd1, float* sd2, float* sx1, const float* sy1, float* sparam);
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void CUBLASWINAPI cublasDrotmg(double* sd1, double* sd2, double* sx1, const double* sy1, double* sparam);
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+
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/* --------------- CUBLAS BLAS2 functions ---------------- */
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/* GEMV */
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void CUBLASWINAPI cublasSgemv(char trans,
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int m,
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int n,
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float alpha,
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const float* A,
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int lda,
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const float* x,
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int incx,
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float beta,
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float* y,
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int incy);
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void CUBLASWINAPI cublasDgemv(char trans,
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int m,
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int n,
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double alpha,
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const double* A,
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int lda,
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const double* x,
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int incx,
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double beta,
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double* y,
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int incy);
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void CUBLASWINAPI cublasCgemv(char trans,
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int m,
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int n,
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cuComplex alpha,
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const cuComplex* A,
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int lda,
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const cuComplex* x,
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int incx,
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cuComplex beta,
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cuComplex* y,
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int incy);
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void CUBLASWINAPI cublasZgemv(char trans,
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int m,
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int n,
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cuDoubleComplex alpha,
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const cuDoubleComplex* A,
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int lda,
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const cuDoubleComplex* x,
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int incx,
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cuDoubleComplex beta,
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cuDoubleComplex* y,
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int incy);
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/*------------------------------------------------------------------------*/
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/* GBMV */
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void CUBLASWINAPI cublasSgbmv(char trans,
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int m,
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int n,
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int kl,
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int ku,
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float alpha,
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const float* A,
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int lda,
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const float* x,
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int incx,
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float beta,
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float* y,
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int incy);
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void CUBLASWINAPI cublasDgbmv(char trans,
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int m,
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+
int n,
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int kl,
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+
int ku,
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252 |
+
double alpha,
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const double* A,
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int lda,
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const double* x,
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+
int incx,
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+
double beta,
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+
double* y,
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int incy);
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void CUBLASWINAPI cublasCgbmv(char trans,
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int m,
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+
int n,
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+
int kl,
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+
int ku,
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+
cuComplex alpha,
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const cuComplex* A,
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int lda,
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+
const cuComplex* x,
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+
int incx,
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+
cuComplex beta,
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+
cuComplex* y,
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+
int incy);
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+
void CUBLASWINAPI cublasZgbmv(char trans,
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+
int m,
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275 |
+
int n,
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276 |
+
int kl,
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277 |
+
int ku,
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+
cuDoubleComplex alpha,
|
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+
const cuDoubleComplex* A,
|
280 |
+
int lda,
|
281 |
+
const cuDoubleComplex* x,
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282 |
+
int incx,
|
283 |
+
cuDoubleComplex beta,
|
284 |
+
cuDoubleComplex* y,
|
285 |
+
int incy);
|
286 |
+
/*------------------------------------------------------------------------*/
|
287 |
+
/* TRMV */
|
288 |
+
void CUBLASWINAPI cublasStrmv(char uplo, char trans, char diag, int n, const float* A, int lda, float* x, int incx);
|
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+
void CUBLASWINAPI cublasDtrmv(char uplo, char trans, char diag, int n, const double* A, int lda, double* x, int incx);
|
290 |
+
void CUBLASWINAPI
|
291 |
+
cublasCtrmv(char uplo, char trans, char diag, int n, const cuComplex* A, int lda, cuComplex* x, int incx);
|
292 |
+
void CUBLASWINAPI
|
293 |
+
cublasZtrmv(char uplo, char trans, char diag, int n, const cuDoubleComplex* A, int lda, cuDoubleComplex* x, int incx);
|
294 |
+
/*------------------------------------------------------------------------*/
|
295 |
+
/* TBMV */
|
296 |
+
void CUBLASWINAPI
|
297 |
+
cublasStbmv(char uplo, char trans, char diag, int n, int k, const float* A, int lda, float* x, int incx);
|
298 |
+
void CUBLASWINAPI
|
299 |
+
cublasDtbmv(char uplo, char trans, char diag, int n, int k, const double* A, int lda, double* x, int incx);
|
300 |
+
void CUBLASWINAPI
|
301 |
+
cublasCtbmv(char uplo, char trans, char diag, int n, int k, const cuComplex* A, int lda, cuComplex* x, int incx);
|
302 |
+
void CUBLASWINAPI cublasZtbmv(
|
303 |
+
char uplo, char trans, char diag, int n, int k, const cuDoubleComplex* A, int lda, cuDoubleComplex* x, int incx);
|
304 |
+
/*------------------------------------------------------------------------*/
|
305 |
+
/* TPMV */
|
306 |
+
void CUBLASWINAPI cublasStpmv(char uplo, char trans, char diag, int n, const float* AP, float* x, int incx);
|
307 |
+
|
308 |
+
void CUBLASWINAPI cublasDtpmv(char uplo, char trans, char diag, int n, const double* AP, double* x, int incx);
|
309 |
+
|
310 |
+
void CUBLASWINAPI cublasCtpmv(char uplo, char trans, char diag, int n, const cuComplex* AP, cuComplex* x, int incx);
|
311 |
+
|
312 |
+
void CUBLASWINAPI
|
313 |
+
cublasZtpmv(char uplo, char trans, char diag, int n, const cuDoubleComplex* AP, cuDoubleComplex* x, int incx);
|
314 |
+
/*------------------------------------------------------------------------*/
|
315 |
+
/* TRSV */
|
316 |
+
void CUBLASWINAPI cublasStrsv(char uplo, char trans, char diag, int n, const float* A, int lda, float* x, int incx);
|
317 |
+
|
318 |
+
void CUBLASWINAPI cublasDtrsv(char uplo, char trans, char diag, int n, const double* A, int lda, double* x, int incx);
|
319 |
+
|
320 |
+
void CUBLASWINAPI
|
321 |
+
cublasCtrsv(char uplo, char trans, char diag, int n, const cuComplex* A, int lda, cuComplex* x, int incx);
|
322 |
+
|
323 |
+
void CUBLASWINAPI
|
324 |
+
cublasZtrsv(char uplo, char trans, char diag, int n, const cuDoubleComplex* A, int lda, cuDoubleComplex* x, int incx);
|
325 |
+
/*------------------------------------------------------------------------*/
|
326 |
+
/* TPSV */
|
327 |
+
void CUBLASWINAPI cublasStpsv(char uplo, char trans, char diag, int n, const float* AP, float* x, int incx);
|
328 |
+
|
329 |
+
void CUBLASWINAPI cublasDtpsv(char uplo, char trans, char diag, int n, const double* AP, double* x, int incx);
|
330 |
+
|
331 |
+
void CUBLASWINAPI cublasCtpsv(char uplo, char trans, char diag, int n, const cuComplex* AP, cuComplex* x, int incx);
|
332 |
+
|
333 |
+
void CUBLASWINAPI
|
334 |
+
cublasZtpsv(char uplo, char trans, char diag, int n, const cuDoubleComplex* AP, cuDoubleComplex* x, int incx);
|
335 |
+
/*------------------------------------------------------------------------*/
|
336 |
+
/* TBSV */
|
337 |
+
void CUBLASWINAPI
|
338 |
+
cublasStbsv(char uplo, char trans, char diag, int n, int k, const float* A, int lda, float* x, int incx);
|
339 |
+
|
340 |
+
void CUBLASWINAPI
|
341 |
+
cublasDtbsv(char uplo, char trans, char diag, int n, int k, const double* A, int lda, double* x, int incx);
|
342 |
+
void CUBLASWINAPI
|
343 |
+
cublasCtbsv(char uplo, char trans, char diag, int n, int k, const cuComplex* A, int lda, cuComplex* x, int incx);
|
344 |
+
|
345 |
+
void CUBLASWINAPI cublasZtbsv(
|
346 |
+
char uplo, char trans, char diag, int n, int k, const cuDoubleComplex* A, int lda, cuDoubleComplex* x, int incx);
|
347 |
+
/*------------------------------------------------------------------------*/
|
348 |
+
/* SYMV/HEMV */
|
349 |
+
void CUBLASWINAPI cublasSsymv(
|
350 |
+
char uplo, int n, float alpha, const float* A, int lda, const float* x, int incx, float beta, float* y, int incy);
|
351 |
+
void CUBLASWINAPI cublasDsymv(char uplo,
|
352 |
+
int n,
|
353 |
+
double alpha,
|
354 |
+
const double* A,
|
355 |
+
int lda,
|
356 |
+
const double* x,
|
357 |
+
int incx,
|
358 |
+
double beta,
|
359 |
+
double* y,
|
360 |
+
int incy);
|
361 |
+
void CUBLASWINAPI cublasChemv(char uplo,
|
362 |
+
int n,
|
363 |
+
cuComplex alpha,
|
364 |
+
const cuComplex* A,
|
365 |
+
int lda,
|
366 |
+
const cuComplex* x,
|
367 |
+
int incx,
|
368 |
+
cuComplex beta,
|
369 |
+
cuComplex* y,
|
370 |
+
int incy);
|
371 |
+
void CUBLASWINAPI cublasZhemv(char uplo,
|
372 |
+
int n,
|
373 |
+
cuDoubleComplex alpha,
|
374 |
+
const cuDoubleComplex* A,
|
375 |
+
int lda,
|
376 |
+
const cuDoubleComplex* x,
|
377 |
+
int incx,
|
378 |
+
cuDoubleComplex beta,
|
379 |
+
cuDoubleComplex* y,
|
380 |
+
int incy);
|
381 |
+
/*------------------------------------------------------------------------*/
|
382 |
+
/* SBMV/HBMV */
|
383 |
+
void CUBLASWINAPI cublasSsbmv(char uplo,
|
384 |
+
int n,
|
385 |
+
int k,
|
386 |
+
float alpha,
|
387 |
+
const float* A,
|
388 |
+
int lda,
|
389 |
+
const float* x,
|
390 |
+
int incx,
|
391 |
+
float beta,
|
392 |
+
float* y,
|
393 |
+
int incy);
|
394 |
+
void CUBLASWINAPI cublasDsbmv(char uplo,
|
395 |
+
int n,
|
396 |
+
int k,
|
397 |
+
double alpha,
|
398 |
+
const double* A,
|
399 |
+
int lda,
|
400 |
+
const double* x,
|
401 |
+
int incx,
|
402 |
+
double beta,
|
403 |
+
double* y,
|
404 |
+
int incy);
|
405 |
+
void CUBLASWINAPI cublasChbmv(char uplo,
|
406 |
+
int n,
|
407 |
+
int k,
|
408 |
+
cuComplex alpha,
|
409 |
+
const cuComplex* A,
|
410 |
+
int lda,
|
411 |
+
const cuComplex* x,
|
412 |
+
int incx,
|
413 |
+
cuComplex beta,
|
414 |
+
cuComplex* y,
|
415 |
+
int incy);
|
416 |
+
void CUBLASWINAPI cublasZhbmv(char uplo,
|
417 |
+
int n,
|
418 |
+
int k,
|
419 |
+
cuDoubleComplex alpha,
|
420 |
+
const cuDoubleComplex* A,
|
421 |
+
int lda,
|
422 |
+
const cuDoubleComplex* x,
|
423 |
+
int incx,
|
424 |
+
cuDoubleComplex beta,
|
425 |
+
cuDoubleComplex* y,
|
426 |
+
int incy);
|
427 |
+
/*------------------------------------------------------------------------*/
|
428 |
+
/* SPMV/HPMV */
|
429 |
+
void CUBLASWINAPI
|
430 |
+
cublasSspmv(char uplo, int n, float alpha, const float* AP, const float* x, int incx, float beta, float* y, int incy);
|
431 |
+
void CUBLASWINAPI cublasDspmv(
|
432 |
+
char uplo, int n, double alpha, const double* AP, const double* x, int incx, double beta, double* y, int incy);
|
433 |
+
void CUBLASWINAPI cublasChpmv(char uplo,
|
434 |
+
int n,
|
435 |
+
cuComplex alpha,
|
436 |
+
const cuComplex* AP,
|
437 |
+
const cuComplex* x,
|
438 |
+
int incx,
|
439 |
+
cuComplex beta,
|
440 |
+
cuComplex* y,
|
441 |
+
int incy);
|
442 |
+
void CUBLASWINAPI cublasZhpmv(char uplo,
|
443 |
+
int n,
|
444 |
+
cuDoubleComplex alpha,
|
445 |
+
const cuDoubleComplex* AP,
|
446 |
+
const cuDoubleComplex* x,
|
447 |
+
int incx,
|
448 |
+
cuDoubleComplex beta,
|
449 |
+
cuDoubleComplex* y,
|
450 |
+
int incy);
|
451 |
+
|
452 |
+
/*------------------------------------------------------------------------*/
|
453 |
+
/* GER */
|
454 |
+
void CUBLASWINAPI
|
455 |
+
cublasSger(int m, int n, float alpha, const float* x, int incx, const float* y, int incy, float* A, int lda);
|
456 |
+
void CUBLASWINAPI
|
457 |
+
cublasDger(int m, int n, double alpha, const double* x, int incx, const double* y, int incy, double* A, int lda);
|
458 |
+
|
459 |
+
void CUBLASWINAPI cublasCgeru(
|
460 |
+
int m, int n, cuComplex alpha, const cuComplex* x, int incx, const cuComplex* y, int incy, cuComplex* A, int lda);
|
461 |
+
void CUBLASWINAPI cublasCgerc(
|
462 |
+
int m, int n, cuComplex alpha, const cuComplex* x, int incx, const cuComplex* y, int incy, cuComplex* A, int lda);
|
463 |
+
void CUBLASWINAPI cublasZgeru(int m,
|
464 |
+
int n,
|
465 |
+
cuDoubleComplex alpha,
|
466 |
+
const cuDoubleComplex* x,
|
467 |
+
int incx,
|
468 |
+
const cuDoubleComplex* y,
|
469 |
+
int incy,
|
470 |
+
cuDoubleComplex* A,
|
471 |
+
int lda);
|
472 |
+
void CUBLASWINAPI cublasZgerc(int m,
|
473 |
+
int n,
|
474 |
+
cuDoubleComplex alpha,
|
475 |
+
const cuDoubleComplex* x,
|
476 |
+
int incx,
|
477 |
+
const cuDoubleComplex* y,
|
478 |
+
int incy,
|
479 |
+
cuDoubleComplex* A,
|
480 |
+
int lda);
|
481 |
+
/*------------------------------------------------------------------------*/
|
482 |
+
/* SYR/HER */
|
483 |
+
void CUBLASWINAPI cublasSsyr(char uplo, int n, float alpha, const float* x, int incx, float* A, int lda);
|
484 |
+
void CUBLASWINAPI cublasDsyr(char uplo, int n, double alpha, const double* x, int incx, double* A, int lda);
|
485 |
+
|
486 |
+
void CUBLASWINAPI cublasCher(char uplo, int n, float alpha, const cuComplex* x, int incx, cuComplex* A, int lda);
|
487 |
+
void CUBLASWINAPI
|
488 |
+
cublasZher(char uplo, int n, double alpha, const cuDoubleComplex* x, int incx, cuDoubleComplex* A, int lda);
|
489 |
+
|
490 |
+
/*------------------------------------------------------------------------*/
|
491 |
+
/* SPR/HPR */
|
492 |
+
void CUBLASWINAPI cublasSspr(char uplo, int n, float alpha, const float* x, int incx, float* AP);
|
493 |
+
void CUBLASWINAPI cublasDspr(char uplo, int n, double alpha, const double* x, int incx, double* AP);
|
494 |
+
void CUBLASWINAPI cublasChpr(char uplo, int n, float alpha, const cuComplex* x, int incx, cuComplex* AP);
|
495 |
+
void CUBLASWINAPI cublasZhpr(char uplo, int n, double alpha, const cuDoubleComplex* x, int incx, cuDoubleComplex* AP);
|
496 |
+
/*------------------------------------------------------------------------*/
|
497 |
+
/* SYR2/HER2 */
|
498 |
+
void CUBLASWINAPI
|
499 |
+
cublasSsyr2(char uplo, int n, float alpha, const float* x, int incx, const float* y, int incy, float* A, int lda);
|
500 |
+
void CUBLASWINAPI
|
501 |
+
cublasDsyr2(char uplo, int n, double alpha, const double* x, int incx, const double* y, int incy, double* A, int lda);
|
502 |
+
void CUBLASWINAPI cublasCher2(char uplo,
|
503 |
+
int n,
|
504 |
+
cuComplex alpha,
|
505 |
+
const cuComplex* x,
|
506 |
+
int incx,
|
507 |
+
const cuComplex* y,
|
508 |
+
int incy,
|
509 |
+
cuComplex* A,
|
510 |
+
int lda);
|
511 |
+
void CUBLASWINAPI cublasZher2(char uplo,
|
512 |
+
int n,
|
513 |
+
cuDoubleComplex alpha,
|
514 |
+
const cuDoubleComplex* x,
|
515 |
+
int incx,
|
516 |
+
const cuDoubleComplex* y,
|
517 |
+
int incy,
|
518 |
+
cuDoubleComplex* A,
|
519 |
+
int lda);
|
520 |
+
|
521 |
+
/*------------------------------------------------------------------------*/
|
522 |
+
/* SPR2/HPR2 */
|
523 |
+
void CUBLASWINAPI
|
524 |
+
cublasSspr2(char uplo, int n, float alpha, const float* x, int incx, const float* y, int incy, float* AP);
|
525 |
+
void CUBLASWINAPI
|
526 |
+
cublasDspr2(char uplo, int n, double alpha, const double* x, int incx, const double* y, int incy, double* AP);
|
527 |
+
void CUBLASWINAPI cublasChpr2(
|
528 |
+
char uplo, int n, cuComplex alpha, const cuComplex* x, int incx, const cuComplex* y, int incy, cuComplex* AP);
|
529 |
+
void CUBLASWINAPI cublasZhpr2(char uplo,
|
530 |
+
int n,
|
531 |
+
cuDoubleComplex alpha,
|
532 |
+
const cuDoubleComplex* x,
|
533 |
+
int incx,
|
534 |
+
const cuDoubleComplex* y,
|
535 |
+
int incy,
|
536 |
+
cuDoubleComplex* AP);
|
537 |
+
/* ------------------------BLAS3 Functions ------------------------------- */
|
538 |
+
/* GEMM */
|
539 |
+
void CUBLASWINAPI cublasSgemm(char transa,
|
540 |
+
char transb,
|
541 |
+
int m,
|
542 |
+
int n,
|
543 |
+
int k,
|
544 |
+
float alpha,
|
545 |
+
const float* A,
|
546 |
+
int lda,
|
547 |
+
const float* B,
|
548 |
+
int ldb,
|
549 |
+
float beta,
|
550 |
+
float* C,
|
551 |
+
int ldc);
|
552 |
+
void CUBLASWINAPI cublasDgemm(char transa,
|
553 |
+
char transb,
|
554 |
+
int m,
|
555 |
+
int n,
|
556 |
+
int k,
|
557 |
+
double alpha,
|
558 |
+
const double* A,
|
559 |
+
int lda,
|
560 |
+
const double* B,
|
561 |
+
int ldb,
|
562 |
+
double beta,
|
563 |
+
double* C,
|
564 |
+
int ldc);
|
565 |
+
void CUBLASWINAPI cublasCgemm(char transa,
|
566 |
+
char transb,
|
567 |
+
int m,
|
568 |
+
int n,
|
569 |
+
int k,
|
570 |
+
cuComplex alpha,
|
571 |
+
const cuComplex* A,
|
572 |
+
int lda,
|
573 |
+
const cuComplex* B,
|
574 |
+
int ldb,
|
575 |
+
cuComplex beta,
|
576 |
+
cuComplex* C,
|
577 |
+
int ldc);
|
578 |
+
void CUBLASWINAPI cublasZgemm(char transa,
|
579 |
+
char transb,
|
580 |
+
int m,
|
581 |
+
int n,
|
582 |
+
int k,
|
583 |
+
cuDoubleComplex alpha,
|
584 |
+
const cuDoubleComplex* A,
|
585 |
+
int lda,
|
586 |
+
const cuDoubleComplex* B,
|
587 |
+
int ldb,
|
588 |
+
cuDoubleComplex beta,
|
589 |
+
cuDoubleComplex* C,
|
590 |
+
int ldc);
|
591 |
+
/* -------------------------------------------------------*/
|
592 |
+
/* SYRK */
|
593 |
+
void CUBLASWINAPI
|
594 |
+
cublasSsyrk(char uplo, char trans, int n, int k, float alpha, const float* A, int lda, float beta, float* C, int ldc);
|
595 |
+
void CUBLASWINAPI cublasDsyrk(
|
596 |
+
char uplo, char trans, int n, int k, double alpha, const double* A, int lda, double beta, double* C, int ldc);
|
597 |
+
|
598 |
+
void CUBLASWINAPI cublasCsyrk(char uplo,
|
599 |
+
char trans,
|
600 |
+
int n,
|
601 |
+
int k,
|
602 |
+
cuComplex alpha,
|
603 |
+
const cuComplex* A,
|
604 |
+
int lda,
|
605 |
+
cuComplex beta,
|
606 |
+
cuComplex* C,
|
607 |
+
int ldc);
|
608 |
+
void CUBLASWINAPI cublasZsyrk(char uplo,
|
609 |
+
char trans,
|
610 |
+
int n,
|
611 |
+
int k,
|
612 |
+
cuDoubleComplex alpha,
|
613 |
+
const cuDoubleComplex* A,
|
614 |
+
int lda,
|
615 |
+
cuDoubleComplex beta,
|
616 |
+
cuDoubleComplex* C,
|
617 |
+
int ldc);
|
618 |
+
/* ------------------------------------------------------- */
|
619 |
+
/* HERK */
|
620 |
+
void CUBLASWINAPI cublasCherk(
|
621 |
+
char uplo, char trans, int n, int k, float alpha, const cuComplex* A, int lda, float beta, cuComplex* C, int ldc);
|
622 |
+
void CUBLASWINAPI cublasZherk(char uplo,
|
623 |
+
char trans,
|
624 |
+
int n,
|
625 |
+
int k,
|
626 |
+
double alpha,
|
627 |
+
const cuDoubleComplex* A,
|
628 |
+
int lda,
|
629 |
+
double beta,
|
630 |
+
cuDoubleComplex* C,
|
631 |
+
int ldc);
|
632 |
+
/* ------------------------------------------------------- */
|
633 |
+
/* SYR2K */
|
634 |
+
void CUBLASWINAPI cublasSsyr2k(char uplo,
|
635 |
+
char trans,
|
636 |
+
int n,
|
637 |
+
int k,
|
638 |
+
float alpha,
|
639 |
+
const float* A,
|
640 |
+
int lda,
|
641 |
+
const float* B,
|
642 |
+
int ldb,
|
643 |
+
float beta,
|
644 |
+
float* C,
|
645 |
+
int ldc);
|
646 |
+
|
647 |
+
void CUBLASWINAPI cublasDsyr2k(char uplo,
|
648 |
+
char trans,
|
649 |
+
int n,
|
650 |
+
int k,
|
651 |
+
double alpha,
|
652 |
+
const double* A,
|
653 |
+
int lda,
|
654 |
+
const double* B,
|
655 |
+
int ldb,
|
656 |
+
double beta,
|
657 |
+
double* C,
|
658 |
+
int ldc);
|
659 |
+
void CUBLASWINAPI cublasCsyr2k(char uplo,
|
660 |
+
char trans,
|
661 |
+
int n,
|
662 |
+
int k,
|
663 |
+
cuComplex alpha,
|
664 |
+
const cuComplex* A,
|
665 |
+
int lda,
|
666 |
+
const cuComplex* B,
|
667 |
+
int ldb,
|
668 |
+
cuComplex beta,
|
669 |
+
cuComplex* C,
|
670 |
+
int ldc);
|
671 |
+
|
672 |
+
void CUBLASWINAPI cublasZsyr2k(char uplo,
|
673 |
+
char trans,
|
674 |
+
int n,
|
675 |
+
int k,
|
676 |
+
cuDoubleComplex alpha,
|
677 |
+
const cuDoubleComplex* A,
|
678 |
+
int lda,
|
679 |
+
const cuDoubleComplex* B,
|
680 |
+
int ldb,
|
681 |
+
cuDoubleComplex beta,
|
682 |
+
cuDoubleComplex* C,
|
683 |
+
int ldc);
|
684 |
+
/* ------------------------------------------------------- */
|
685 |
+
/* HER2K */
|
686 |
+
void CUBLASWINAPI cublasCher2k(char uplo,
|
687 |
+
char trans,
|
688 |
+
int n,
|
689 |
+
int k,
|
690 |
+
cuComplex alpha,
|
691 |
+
const cuComplex* A,
|
692 |
+
int lda,
|
693 |
+
const cuComplex* B,
|
694 |
+
int ldb,
|
695 |
+
float beta,
|
696 |
+
cuComplex* C,
|
697 |
+
int ldc);
|
698 |
+
|
699 |
+
void CUBLASWINAPI cublasZher2k(char uplo,
|
700 |
+
char trans,
|
701 |
+
int n,
|
702 |
+
int k,
|
703 |
+
cuDoubleComplex alpha,
|
704 |
+
const cuDoubleComplex* A,
|
705 |
+
int lda,
|
706 |
+
const cuDoubleComplex* B,
|
707 |
+
int ldb,
|
708 |
+
double beta,
|
709 |
+
cuDoubleComplex* C,
|
710 |
+
int ldc);
|
711 |
+
|
712 |
+
/*------------------------------------------------------------------------*/
|
713 |
+
/* SYMM*/
|
714 |
+
void CUBLASWINAPI cublasSsymm(char side,
|
715 |
+
char uplo,
|
716 |
+
int m,
|
717 |
+
int n,
|
718 |
+
float alpha,
|
719 |
+
const float* A,
|
720 |
+
int lda,
|
721 |
+
const float* B,
|
722 |
+
int ldb,
|
723 |
+
float beta,
|
724 |
+
float* C,
|
725 |
+
int ldc);
|
726 |
+
void CUBLASWINAPI cublasDsymm(char side,
|
727 |
+
char uplo,
|
728 |
+
int m,
|
729 |
+
int n,
|
730 |
+
double alpha,
|
731 |
+
const double* A,
|
732 |
+
int lda,
|
733 |
+
const double* B,
|
734 |
+
int ldb,
|
735 |
+
double beta,
|
736 |
+
double* C,
|
737 |
+
int ldc);
|
738 |
+
|
739 |
+
void CUBLASWINAPI cublasCsymm(char side,
|
740 |
+
char uplo,
|
741 |
+
int m,
|
742 |
+
int n,
|
743 |
+
cuComplex alpha,
|
744 |
+
const cuComplex* A,
|
745 |
+
int lda,
|
746 |
+
const cuComplex* B,
|
747 |
+
int ldb,
|
748 |
+
cuComplex beta,
|
749 |
+
cuComplex* C,
|
750 |
+
int ldc);
|
751 |
+
|
752 |
+
void CUBLASWINAPI cublasZsymm(char side,
|
753 |
+
char uplo,
|
754 |
+
int m,
|
755 |
+
int n,
|
756 |
+
cuDoubleComplex alpha,
|
757 |
+
const cuDoubleComplex* A,
|
758 |
+
int lda,
|
759 |
+
const cuDoubleComplex* B,
|
760 |
+
int ldb,
|
761 |
+
cuDoubleComplex beta,
|
762 |
+
cuDoubleComplex* C,
|
763 |
+
int ldc);
|
764 |
+
/*------------------------------------------------------------------------*/
|
765 |
+
/* HEMM*/
|
766 |
+
void CUBLASWINAPI cublasChemm(char side,
|
767 |
+
char uplo,
|
768 |
+
int m,
|
769 |
+
int n,
|
770 |
+
cuComplex alpha,
|
771 |
+
const cuComplex* A,
|
772 |
+
int lda,
|
773 |
+
const cuComplex* B,
|
774 |
+
int ldb,
|
775 |
+
cuComplex beta,
|
776 |
+
cuComplex* C,
|
777 |
+
int ldc);
|
778 |
+
void CUBLASWINAPI cublasZhemm(char side,
|
779 |
+
char uplo,
|
780 |
+
int m,
|
781 |
+
int n,
|
782 |
+
cuDoubleComplex alpha,
|
783 |
+
const cuDoubleComplex* A,
|
784 |
+
int lda,
|
785 |
+
const cuDoubleComplex* B,
|
786 |
+
int ldb,
|
787 |
+
cuDoubleComplex beta,
|
788 |
+
cuDoubleComplex* C,
|
789 |
+
int ldc);
|
790 |
+
|
791 |
+
/*------------------------------------------------------------------------*/
|
792 |
+
/* TRSM*/
|
793 |
+
void CUBLASWINAPI cublasStrsm(char side,
|
794 |
+
char uplo,
|
795 |
+
char transa,
|
796 |
+
char diag,
|
797 |
+
int m,
|
798 |
+
int n,
|
799 |
+
float alpha,
|
800 |
+
const float* A,
|
801 |
+
int lda,
|
802 |
+
float* B,
|
803 |
+
int ldb);
|
804 |
+
|
805 |
+
void CUBLASWINAPI cublasDtrsm(char side,
|
806 |
+
char uplo,
|
807 |
+
char transa,
|
808 |
+
char diag,
|
809 |
+
int m,
|
810 |
+
int n,
|
811 |
+
double alpha,
|
812 |
+
const double* A,
|
813 |
+
int lda,
|
814 |
+
double* B,
|
815 |
+
int ldb);
|
816 |
+
|
817 |
+
void CUBLASWINAPI cublasCtrsm(char side,
|
818 |
+
char uplo,
|
819 |
+
char transa,
|
820 |
+
char diag,
|
821 |
+
int m,
|
822 |
+
int n,
|
823 |
+
cuComplex alpha,
|
824 |
+
const cuComplex* A,
|
825 |
+
int lda,
|
826 |
+
cuComplex* B,
|
827 |
+
int ldb);
|
828 |
+
|
829 |
+
void CUBLASWINAPI cublasZtrsm(char side,
|
830 |
+
char uplo,
|
831 |
+
char transa,
|
832 |
+
char diag,
|
833 |
+
int m,
|
834 |
+
int n,
|
835 |
+
cuDoubleComplex alpha,
|
836 |
+
const cuDoubleComplex* A,
|
837 |
+
int lda,
|
838 |
+
cuDoubleComplex* B,
|
839 |
+
int ldb);
|
840 |
+
/*------------------------------------------------------------------------*/
|
841 |
+
/* TRMM*/
|
842 |
+
void CUBLASWINAPI cublasStrmm(char side,
|
843 |
+
char uplo,
|
844 |
+
char transa,
|
845 |
+
char diag,
|
846 |
+
int m,
|
847 |
+
int n,
|
848 |
+
float alpha,
|
849 |
+
const float* A,
|
850 |
+
int lda,
|
851 |
+
float* B,
|
852 |
+
int ldb);
|
853 |
+
void CUBLASWINAPI cublasDtrmm(char side,
|
854 |
+
char uplo,
|
855 |
+
char transa,
|
856 |
+
char diag,
|
857 |
+
int m,
|
858 |
+
int n,
|
859 |
+
double alpha,
|
860 |
+
const double* A,
|
861 |
+
int lda,
|
862 |
+
double* B,
|
863 |
+
int ldb);
|
864 |
+
void CUBLASWINAPI cublasCtrmm(char side,
|
865 |
+
char uplo,
|
866 |
+
char transa,
|
867 |
+
char diag,
|
868 |
+
int m,
|
869 |
+
int n,
|
870 |
+
cuComplex alpha,
|
871 |
+
const cuComplex* A,
|
872 |
+
int lda,
|
873 |
+
cuComplex* B,
|
874 |
+
int ldb);
|
875 |
+
void CUBLASWINAPI cublasZtrmm(char side,
|
876 |
+
char uplo,
|
877 |
+
char transa,
|
878 |
+
char diag,
|
879 |
+
int m,
|
880 |
+
int n,
|
881 |
+
cuDoubleComplex alpha,
|
882 |
+
const cuDoubleComplex* A,
|
883 |
+
int lda,
|
884 |
+
cuDoubleComplex* B,
|
885 |
+
int ldb);
|
886 |
+
|
887 |
+
#if defined(__cplusplus)
|
888 |
+
}
|
889 |
+
#endif /* __cplusplus */
|
890 |
+
|
891 |
+
#endif /* !defined(CUBLAS_H_) */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublasLt.h
ADDED
@@ -0,0 +1,1815 @@
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|
1 |
+
/*
|
2 |
+
* Copyright 1993-2022 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
#pragma once
|
50 |
+
|
51 |
+
#ifndef CUBLASAPI
|
52 |
+
#ifdef __CUDACC__
|
53 |
+
#define CUBLASAPI __host__ __device__
|
54 |
+
#else
|
55 |
+
#define CUBLASAPI
|
56 |
+
#endif
|
57 |
+
#endif
|
58 |
+
|
59 |
+
#include <cublas_api.h>
|
60 |
+
|
61 |
+
#include <stdint.h>
|
62 |
+
#include <stddef.h>
|
63 |
+
#include <stdio.h>
|
64 |
+
|
65 |
+
#if defined(__cplusplus)
|
66 |
+
extern "C" {
|
67 |
+
#endif /* __cplusplus */
|
68 |
+
|
69 |
+
/** Opaque structure holding CUBLASLT context
|
70 |
+
*/
|
71 |
+
typedef struct cublasLtContext* cublasLtHandle_t;
|
72 |
+
|
73 |
+
cublasStatus_t CUBLASWINAPI cublasLtCreate(cublasLtHandle_t* lightHandle);
|
74 |
+
|
75 |
+
cublasStatus_t CUBLASWINAPI cublasLtDestroy(cublasLtHandle_t lightHandle);
|
76 |
+
|
77 |
+
const char* CUBLASWINAPI cublasLtGetStatusName(cublasStatus_t status);
|
78 |
+
|
79 |
+
const char* CUBLASWINAPI cublasLtGetStatusString(cublasStatus_t status);
|
80 |
+
|
81 |
+
size_t CUBLASWINAPI cublasLtGetVersion(void);
|
82 |
+
|
83 |
+
size_t CUBLASWINAPI cublasLtGetCudartVersion(void);
|
84 |
+
|
85 |
+
cublasStatus_t CUBLASWINAPI cublasLtGetProperty(libraryPropertyType type, int* value);
|
86 |
+
|
87 |
+
cublasStatus_t CUBLASWINAPI cublasLtHeuristicsCacheGetCapacity(size_t* capacity);
|
88 |
+
cublasStatus_t CUBLASWINAPI cublasLtHeuristicsCacheSetCapacity(size_t capacity);
|
89 |
+
|
90 |
+
/** Restricts usage of CPU instructions (ISA) specified by the flags in the mask.
|
91 |
+
*
|
92 |
+
* Flags can be combined with bitwise OR(|) operator. Supported flags:
|
93 |
+
* - 0x1 -- x86-64 AVX512 ISA
|
94 |
+
*
|
95 |
+
* Default mask: 0 (any applicable ISA is allowed).
|
96 |
+
*
|
97 |
+
* The function returns the previous value of the mask.
|
98 |
+
* The function takes precedence over the environment variable CUBLASLT_DISABLE_CPU_INSTRUCTIONS_MASK.
|
99 |
+
*/
|
100 |
+
unsigned CUBLASWINAPI cublasLtDisableCpuInstructionsSetMask(unsigned mask);
|
101 |
+
|
102 |
+
/** Semi-opaque descriptor for matrix memory layout
|
103 |
+
*/
|
104 |
+
typedef struct {
|
105 |
+
uint64_t data[8];
|
106 |
+
} cublasLtMatrixLayoutOpaque_t;
|
107 |
+
|
108 |
+
/** Opaque descriptor for matrix memory layout
|
109 |
+
*/
|
110 |
+
typedef cublasLtMatrixLayoutOpaque_t* cublasLtMatrixLayout_t;
|
111 |
+
|
112 |
+
/** Semi-opaque algorithm descriptor (to avoid complicated alloc/free schemes)
|
113 |
+
*
|
114 |
+
* This structure can be trivially serialized and later restored for use with the same version of cuBLAS library to save
|
115 |
+
* on selecting the right configuration again.
|
116 |
+
*/
|
117 |
+
typedef struct {
|
118 |
+
uint64_t data[8];
|
119 |
+
} cublasLtMatmulAlgo_t;
|
120 |
+
|
121 |
+
/** Semi-opaque descriptor for cublasLtMatmul() operation details
|
122 |
+
*/
|
123 |
+
typedef struct {
|
124 |
+
uint64_t data[23];
|
125 |
+
} cublasLtMatmulDescOpaque_t;
|
126 |
+
|
127 |
+
/** Opaque descriptor for cublasLtMatmul() operation details
|
128 |
+
*/
|
129 |
+
typedef cublasLtMatmulDescOpaque_t* cublasLtMatmulDesc_t;
|
130 |
+
|
131 |
+
/** Semi-opaque descriptor for cublasLtMatrixTransform() operation details
|
132 |
+
*/
|
133 |
+
typedef struct {
|
134 |
+
uint64_t data[8];
|
135 |
+
} cublasLtMatrixTransformDescOpaque_t;
|
136 |
+
|
137 |
+
/** Opaque descriptor for cublasLtMatrixTransform() operation details
|
138 |
+
*/
|
139 |
+
typedef cublasLtMatrixTransformDescOpaque_t* cublasLtMatrixTransformDesc_t;
|
140 |
+
|
141 |
+
/** Semi-opaque descriptor for cublasLtMatmulPreference() operation details
|
142 |
+
*/
|
143 |
+
typedef struct {
|
144 |
+
uint64_t data[8];
|
145 |
+
} cublasLtMatmulPreferenceOpaque_t;
|
146 |
+
|
147 |
+
/** Opaque descriptor for cublasLtMatmulAlgoGetHeuristic() configuration
|
148 |
+
*/
|
149 |
+
typedef cublasLtMatmulPreferenceOpaque_t* cublasLtMatmulPreference_t;
|
150 |
+
|
151 |
+
/** Tile size (in C/D matrix Rows x Cols)
|
152 |
+
*
|
153 |
+
* General order of tile IDs is sorted by size first and by first dimension second.
|
154 |
+
*/
|
155 |
+
typedef enum {
|
156 |
+
CUBLASLT_MATMUL_TILE_UNDEFINED = 0,
|
157 |
+
CUBLASLT_MATMUL_TILE_8x8 = 1,
|
158 |
+
CUBLASLT_MATMUL_TILE_8x16 = 2,
|
159 |
+
CUBLASLT_MATMUL_TILE_16x8 = 3,
|
160 |
+
CUBLASLT_MATMUL_TILE_8x32 = 4,
|
161 |
+
CUBLASLT_MATMUL_TILE_16x16 = 5,
|
162 |
+
CUBLASLT_MATMUL_TILE_32x8 = 6,
|
163 |
+
CUBLASLT_MATMUL_TILE_8x64 = 7,
|
164 |
+
CUBLASLT_MATMUL_TILE_16x32 = 8,
|
165 |
+
CUBLASLT_MATMUL_TILE_32x16 = 9,
|
166 |
+
CUBLASLT_MATMUL_TILE_64x8 = 10,
|
167 |
+
CUBLASLT_MATMUL_TILE_32x32 = 11,
|
168 |
+
CUBLASLT_MATMUL_TILE_32x64 = 12,
|
169 |
+
CUBLASLT_MATMUL_TILE_64x32 = 13,
|
170 |
+
CUBLASLT_MATMUL_TILE_32x128 = 14,
|
171 |
+
CUBLASLT_MATMUL_TILE_64x64 = 15,
|
172 |
+
CUBLASLT_MATMUL_TILE_128x32 = 16,
|
173 |
+
CUBLASLT_MATMUL_TILE_64x128 = 17,
|
174 |
+
CUBLASLT_MATMUL_TILE_128x64 = 18,
|
175 |
+
CUBLASLT_MATMUL_TILE_64x256 = 19,
|
176 |
+
CUBLASLT_MATMUL_TILE_128x128 = 20,
|
177 |
+
CUBLASLT_MATMUL_TILE_256x64 = 21,
|
178 |
+
CUBLASLT_MATMUL_TILE_64x512 = 22,
|
179 |
+
CUBLASLT_MATMUL_TILE_128x256 = 23,
|
180 |
+
CUBLASLT_MATMUL_TILE_256x128 = 24,
|
181 |
+
CUBLASLT_MATMUL_TILE_512x64 = 25,
|
182 |
+
CUBLASLT_MATMUL_TILE_64x96 = 26,
|
183 |
+
CUBLASLT_MATMUL_TILE_96x64 = 27,
|
184 |
+
CUBLASLT_MATMUL_TILE_96x128 = 28,
|
185 |
+
CUBLASLT_MATMUL_TILE_128x160 = 29,
|
186 |
+
CUBLASLT_MATMUL_TILE_160x128 = 30,
|
187 |
+
CUBLASLT_MATMUL_TILE_192x128 = 31,
|
188 |
+
CUBLASLT_MATMUL_TILE_128x192 = 32,
|
189 |
+
CUBLASLT_MATMUL_TILE_128x96 = 33,
|
190 |
+
CUBLASLT_MATMUL_TILE_32x256 = 34,
|
191 |
+
CUBLASLT_MATMUL_TILE_256x32 = 35,
|
192 |
+
CUBLASLT_MATMUL_TILE_END
|
193 |
+
} cublasLtMatmulTile_t;
|
194 |
+
|
195 |
+
/** Size and number of stages in which elements are read into shared memory
|
196 |
+
*
|
197 |
+
* General order of stages IDs is sorted by stage size first and by number of stages second.
|
198 |
+
*/
|
199 |
+
typedef enum {
|
200 |
+
CUBLASLT_MATMUL_STAGES_UNDEFINED = 0,
|
201 |
+
CUBLASLT_MATMUL_STAGES_16x1 = 1,
|
202 |
+
CUBLASLT_MATMUL_STAGES_16x2 = 2,
|
203 |
+
CUBLASLT_MATMUL_STAGES_16x3 = 3,
|
204 |
+
CUBLASLT_MATMUL_STAGES_16x4 = 4,
|
205 |
+
CUBLASLT_MATMUL_STAGES_16x5 = 5,
|
206 |
+
CUBLASLT_MATMUL_STAGES_16x6 = 6,
|
207 |
+
CUBLASLT_MATMUL_STAGES_32x1 = 7,
|
208 |
+
CUBLASLT_MATMUL_STAGES_32x2 = 8,
|
209 |
+
CUBLASLT_MATMUL_STAGES_32x3 = 9,
|
210 |
+
CUBLASLT_MATMUL_STAGES_32x4 = 10,
|
211 |
+
CUBLASLT_MATMUL_STAGES_32x5 = 11,
|
212 |
+
CUBLASLT_MATMUL_STAGES_32x6 = 12,
|
213 |
+
CUBLASLT_MATMUL_STAGES_64x1 = 13,
|
214 |
+
CUBLASLT_MATMUL_STAGES_64x2 = 14,
|
215 |
+
CUBLASLT_MATMUL_STAGES_64x3 = 15,
|
216 |
+
CUBLASLT_MATMUL_STAGES_64x4 = 16,
|
217 |
+
CUBLASLT_MATMUL_STAGES_64x5 = 17,
|
218 |
+
CUBLASLT_MATMUL_STAGES_64x6 = 18,
|
219 |
+
CUBLASLT_MATMUL_STAGES_128x1 = 19,
|
220 |
+
CUBLASLT_MATMUL_STAGES_128x2 = 20,
|
221 |
+
CUBLASLT_MATMUL_STAGES_128x3 = 21,
|
222 |
+
CUBLASLT_MATMUL_STAGES_128x4 = 22,
|
223 |
+
CUBLASLT_MATMUL_STAGES_128x5 = 23,
|
224 |
+
CUBLASLT_MATMUL_STAGES_128x6 = 24,
|
225 |
+
CUBLASLT_MATMUL_STAGES_32x10 = 25,
|
226 |
+
CUBLASLT_MATMUL_STAGES_8x4 = 26,
|
227 |
+
CUBLASLT_MATMUL_STAGES_16x10 = 27,
|
228 |
+
CUBLASLT_MATMUL_STAGES_8x5 = 28,
|
229 |
+
CUBLASLT_MATMUL_STAGES_8x3 = 31,
|
230 |
+
CUBLASLT_MATMUL_STAGES_8xAUTO = 32,
|
231 |
+
CUBLASLT_MATMUL_STAGES_16xAUTO = 33,
|
232 |
+
CUBLASLT_MATMUL_STAGES_32xAUTO = 34,
|
233 |
+
CUBLASLT_MATMUL_STAGES_64xAUTO = 35,
|
234 |
+
CUBLASLT_MATMUL_STAGES_128xAUTO = 36,
|
235 |
+
CUBLASLT_MATMUL_STAGES_END
|
236 |
+
} cublasLtMatmulStages_t;
|
237 |
+
|
238 |
+
/** Thread Block Cluster size
|
239 |
+
*
|
240 |
+
* Typically dimensioned similar to cublasLtMatmulTile_t, with the third coordinate unused at this time.
|
241 |
+
*/
|
242 |
+
typedef enum {
|
243 |
+
/** Let library pick cluster shape automatically */
|
244 |
+
CUBLASLT_CLUSTER_SHAPE_AUTO = 0,
|
245 |
+
CUBLASLT_CLUSTER_SHAPE_1x1x1 = 2,
|
246 |
+
CUBLASLT_CLUSTER_SHAPE_2x1x1 = 3,
|
247 |
+
CUBLASLT_CLUSTER_SHAPE_4x1x1 = 4,
|
248 |
+
CUBLASLT_CLUSTER_SHAPE_1x2x1 = 5,
|
249 |
+
CUBLASLT_CLUSTER_SHAPE_2x2x1 = 6,
|
250 |
+
CUBLASLT_CLUSTER_SHAPE_4x2x1 = 7,
|
251 |
+
CUBLASLT_CLUSTER_SHAPE_1x4x1 = 8,
|
252 |
+
CUBLASLT_CLUSTER_SHAPE_2x4x1 = 9,
|
253 |
+
CUBLASLT_CLUSTER_SHAPE_4x4x1 = 10,
|
254 |
+
CUBLASLT_CLUSTER_SHAPE_8x1x1 = 11,
|
255 |
+
CUBLASLT_CLUSTER_SHAPE_1x8x1 = 12,
|
256 |
+
CUBLASLT_CLUSTER_SHAPE_8x2x1 = 13,
|
257 |
+
CUBLASLT_CLUSTER_SHAPE_2x8x1 = 14,
|
258 |
+
CUBLASLT_CLUSTER_SHAPE_16x1x1 = 15,
|
259 |
+
CUBLASLT_CLUSTER_SHAPE_1x16x1 = 16,
|
260 |
+
CUBLASLT_CLUSTER_SHAPE_3x1x1 = 17,
|
261 |
+
CUBLASLT_CLUSTER_SHAPE_5x1x1 = 18,
|
262 |
+
CUBLASLT_CLUSTER_SHAPE_6x1x1 = 19,
|
263 |
+
CUBLASLT_CLUSTER_SHAPE_7x1x1 = 20,
|
264 |
+
CUBLASLT_CLUSTER_SHAPE_9x1x1 = 21,
|
265 |
+
CUBLASLT_CLUSTER_SHAPE_10x1x1 = 22,
|
266 |
+
CUBLASLT_CLUSTER_SHAPE_11x1x1 = 23,
|
267 |
+
CUBLASLT_CLUSTER_SHAPE_12x1x1 = 24,
|
268 |
+
CUBLASLT_CLUSTER_SHAPE_13x1x1 = 25,
|
269 |
+
CUBLASLT_CLUSTER_SHAPE_14x1x1 = 26,
|
270 |
+
CUBLASLT_CLUSTER_SHAPE_15x1x1 = 27,
|
271 |
+
CUBLASLT_CLUSTER_SHAPE_3x2x1 = 28,
|
272 |
+
CUBLASLT_CLUSTER_SHAPE_5x2x1 = 29,
|
273 |
+
CUBLASLT_CLUSTER_SHAPE_6x2x1 = 30,
|
274 |
+
CUBLASLT_CLUSTER_SHAPE_7x2x1 = 31,
|
275 |
+
CUBLASLT_CLUSTER_SHAPE_1x3x1 = 32,
|
276 |
+
CUBLASLT_CLUSTER_SHAPE_2x3x1 = 33,
|
277 |
+
CUBLASLT_CLUSTER_SHAPE_3x3x1 = 34,
|
278 |
+
CUBLASLT_CLUSTER_SHAPE_4x3x1 = 35,
|
279 |
+
CUBLASLT_CLUSTER_SHAPE_5x3x1 = 36,
|
280 |
+
CUBLASLT_CLUSTER_SHAPE_3x4x1 = 37,
|
281 |
+
CUBLASLT_CLUSTER_SHAPE_1x5x1 = 38,
|
282 |
+
CUBLASLT_CLUSTER_SHAPE_2x5x1 = 39,
|
283 |
+
CUBLASLT_CLUSTER_SHAPE_3x5x1 = 40,
|
284 |
+
CUBLASLT_CLUSTER_SHAPE_1x6x1 = 41,
|
285 |
+
CUBLASLT_CLUSTER_SHAPE_2x6x1 = 42,
|
286 |
+
CUBLASLT_CLUSTER_SHAPE_1x7x1 = 43,
|
287 |
+
CUBLASLT_CLUSTER_SHAPE_2x7x1 = 44,
|
288 |
+
CUBLASLT_CLUSTER_SHAPE_1x9x1 = 45,
|
289 |
+
CUBLASLT_CLUSTER_SHAPE_1x10x1 = 46,
|
290 |
+
CUBLASLT_CLUSTER_SHAPE_1x11x1 = 47,
|
291 |
+
CUBLASLT_CLUSTER_SHAPE_1x12x1 = 48,
|
292 |
+
CUBLASLT_CLUSTER_SHAPE_1x13x1 = 49,
|
293 |
+
CUBLASLT_CLUSTER_SHAPE_1x14x1 = 50,
|
294 |
+
CUBLASLT_CLUSTER_SHAPE_1x15x1 = 51,
|
295 |
+
CUBLASLT_CLUSTER_SHAPE_END
|
296 |
+
} cublasLtClusterShape_t;
|
297 |
+
|
298 |
+
/** Inner size of the kernel
|
299 |
+
*
|
300 |
+
* Represents various aspects of internal kernel design, that don't impact CUDA grid size but may have other more subtle
|
301 |
+
* effects.
|
302 |
+
*
|
303 |
+
*/
|
304 |
+
typedef enum {
|
305 |
+
CUBLASLT_MATMUL_INNER_SHAPE_UNDEFINED = 0,
|
306 |
+
CUBLASLT_MATMUL_INNER_SHAPE_MMA884 = 1,
|
307 |
+
CUBLASLT_MATMUL_INNER_SHAPE_MMA1684 = 2,
|
308 |
+
CUBLASLT_MATMUL_INNER_SHAPE_MMA1688 = 3,
|
309 |
+
CUBLASLT_MATMUL_INNER_SHAPE_MMA16816 = 4,
|
310 |
+
CUBLASLT_MATMUL_INNER_SHAPE_END
|
311 |
+
} cublasLtMatmulInnerShape_t;
|
312 |
+
|
313 |
+
/** Pointer mode to use for alpha/beta */
|
314 |
+
typedef enum {
|
315 |
+
/** matches CUBLAS_POINTER_MODE_HOST, pointer targets a single value host memory */
|
316 |
+
CUBLASLT_POINTER_MODE_HOST = CUBLAS_POINTER_MODE_HOST,
|
317 |
+
/** matches CUBLAS_POINTER_MODE_DEVICE, pointer targets a single value device memory */
|
318 |
+
CUBLASLT_POINTER_MODE_DEVICE = CUBLAS_POINTER_MODE_DEVICE,
|
319 |
+
/** pointer targets an array in device memory */
|
320 |
+
CUBLASLT_POINTER_MODE_DEVICE_VECTOR = 2,
|
321 |
+
/** alpha pointer targets an array in device memory, beta is zero. Note:
|
322 |
+
CUBLASLT_MATMUL_DESC_ALPHA_VECTOR_BATCH_STRIDE is not supported, must be 0. */
|
323 |
+
CUBLASLT_POINTER_MODE_ALPHA_DEVICE_VECTOR_BETA_ZERO = 3,
|
324 |
+
/** alpha pointer targets an array in device memory, beta is a single value in host memory. */
|
325 |
+
CUBLASLT_POINTER_MODE_ALPHA_DEVICE_VECTOR_BETA_HOST = 4,
|
326 |
+
} cublasLtPointerMode_t;
|
327 |
+
|
328 |
+
/** Mask to define pointer mode capability */
|
329 |
+
typedef enum {
|
330 |
+
/** see CUBLASLT_POINTER_MODE_HOST */
|
331 |
+
CUBLASLT_POINTER_MODE_MASK_HOST = 1,
|
332 |
+
/** see CUBLASLT_POINTER_MODE_DEVICE */
|
333 |
+
CUBLASLT_POINTER_MODE_MASK_DEVICE = 2,
|
334 |
+
/** see CUBLASLT_POINTER_MODE_DEVICE_VECTOR */
|
335 |
+
CUBLASLT_POINTER_MODE_MASK_DEVICE_VECTOR = 4,
|
336 |
+
/** see CUBLASLT_POINTER_MODE_ALPHA_DEVICE_VECTOR_BETA_ZERO */
|
337 |
+
CUBLASLT_POINTER_MODE_MASK_ALPHA_DEVICE_VECTOR_BETA_ZERO = 8,
|
338 |
+
/** see CUBLASLT_POINTER_MODE_ALPHA_DEVICE_VECTOR_BETA_HOST */
|
339 |
+
CUBLASLT_POINTER_MODE_MASK_ALPHA_DEVICE_VECTOR_BETA_HOST = 16,
|
340 |
+
} cublasLtPointerModeMask_t;
|
341 |
+
|
342 |
+
/** Implementation details that may affect numerical behavior of algorithms. */
|
343 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_FMA (0x01ull << 0)
|
344 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_HMMA (0x02ull << 0)
|
345 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_IMMA (0x04ull << 0)
|
346 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_DMMA (0x08ull << 0)
|
347 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_TENSOR_OP_MASK (0xfeull << 0)
|
348 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_OP_TYPE_MASK (0xffull << 0)
|
349 |
+
|
350 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_ACCUMULATOR_16F (0x01ull << 8)
|
351 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_ACCUMULATOR_32F (0x02ull << 8)
|
352 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_ACCUMULATOR_64F (0x04ull << 8)
|
353 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_ACCUMULATOR_32I (0x08ull << 8)
|
354 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_ACCUMULATOR_TYPE_MASK (0xffull << 8)
|
355 |
+
|
356 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_16F (0x01ull << 16)
|
357 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_16BF (0x02ull << 16)
|
358 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_TF32 (0x04ull << 16)
|
359 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_32F (0x08ull << 16)
|
360 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_64F (0x10ull << 16)
|
361 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_8I (0x20ull << 16)
|
362 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_8F_E4M3 (0x40ull << 16)
|
363 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_INPUT_8F_E5M2 (0x80ull << 16)
|
364 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_OP_INPUT_TYPE_MASK (0xffull << 16)
|
365 |
+
|
366 |
+
#define CUBLASLT_NUMERICAL_IMPL_FLAGS_GAUSSIAN (0x01ull << 32)
|
367 |
+
typedef uint64_t cublasLtNumericalImplFlags_t;
|
368 |
+
|
369 |
+
/** Execute matrix multiplication (D = alpha * op(A) * op(B) + beta * C).
|
370 |
+
*
|
371 |
+
* \retval CUBLAS_STATUS_NOT_INITIALIZED if cuBLASLt handle has not been initialized
|
372 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if parameters are in conflict or in an impossible configuration; e.g.
|
373 |
+
* when workspaceSizeInBytes is less than workspace required by configured
|
374 |
+
* algo
|
375 |
+
* \retval CUBLAS_STATUS_NOT_SUPPORTED if current implementation on selected device doesn't support configured
|
376 |
+
* operation
|
377 |
+
* \retval CUBLAS_STATUS_ARCH_MISMATCH if configured operation cannot be run using selected device
|
378 |
+
* \retval CUBLAS_STATUS_EXECUTION_FAILED if cuda reported execution error from the device
|
379 |
+
* \retval CUBLAS_STATUS_SUCCESS if the operation completed successfully
|
380 |
+
*/
|
381 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmul(cublasLtHandle_t lightHandle,
|
382 |
+
cublasLtMatmulDesc_t computeDesc,
|
383 |
+
const void* alpha, /* host or device pointer */
|
384 |
+
const void* A,
|
385 |
+
cublasLtMatrixLayout_t Adesc,
|
386 |
+
const void* B,
|
387 |
+
cublasLtMatrixLayout_t Bdesc,
|
388 |
+
const void* beta, /* host or device pointer */
|
389 |
+
const void* C,
|
390 |
+
cublasLtMatrixLayout_t Cdesc,
|
391 |
+
void* D,
|
392 |
+
cublasLtMatrixLayout_t Ddesc,
|
393 |
+
const cublasLtMatmulAlgo_t* algo,
|
394 |
+
void* workspace,
|
395 |
+
size_t workspaceSizeInBytes,
|
396 |
+
cudaStream_t stream);
|
397 |
+
|
398 |
+
/** Matrix layout conversion helper (C = alpha * op(A) + beta * op(B))
|
399 |
+
*
|
400 |
+
* Can be used to change memory order of data or to scale and shift the values.
|
401 |
+
*
|
402 |
+
* \retval CUBLAS_STATUS_NOT_INITIALIZED if cuBLASLt handle has not been initialized
|
403 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if parameters are in conflict or in an impossible configuration; e.g.
|
404 |
+
* when A is not NULL, but Adesc is NULL
|
405 |
+
* \retval CUBLAS_STATUS_NOT_SUPPORTED if current implementation on selected device doesn't support configured
|
406 |
+
* operation
|
407 |
+
* \retval CUBLAS_STATUS_ARCH_MISMATCH if configured operation cannot be run using selected device
|
408 |
+
* \retval CUBLAS_STATUS_EXECUTION_FAILED if cuda reported execution error from the device
|
409 |
+
* \retval CUBLAS_STATUS_SUCCESS if the operation completed successfully
|
410 |
+
*/
|
411 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixTransform(cublasLtHandle_t lightHandle,
|
412 |
+
cublasLtMatrixTransformDesc_t transformDesc,
|
413 |
+
const void* alpha, /* host or device pointer */
|
414 |
+
const void* A,
|
415 |
+
cublasLtMatrixLayout_t Adesc,
|
416 |
+
const void* beta, /* host or device pointer */
|
417 |
+
const void* B,
|
418 |
+
cublasLtMatrixLayout_t Bdesc,
|
419 |
+
void* C,
|
420 |
+
cublasLtMatrixLayout_t Cdesc,
|
421 |
+
cudaStream_t stream);
|
422 |
+
|
423 |
+
/* ---------------------------------------------------------------------------------------*/
|
424 |
+
/* Helper functions for cublasLtMatrixLayout_t */
|
425 |
+
/* ---------------------------------------------------------------------------------------*/
|
426 |
+
|
427 |
+
/** Enum for data ordering */
|
428 |
+
typedef enum {
|
429 |
+
/** Column-major
|
430 |
+
*
|
431 |
+
* Leading dimension is the stride (in elements) to the beginning of next column in memory.
|
432 |
+
*/
|
433 |
+
CUBLASLT_ORDER_COL = 0,
|
434 |
+
/** Row major
|
435 |
+
*
|
436 |
+
* Leading dimension is the stride (in elements) to the beginning of next row in memory.
|
437 |
+
*/
|
438 |
+
CUBLASLT_ORDER_ROW = 1,
|
439 |
+
/** Column-major ordered tiles of 32 columns.
|
440 |
+
*
|
441 |
+
* Leading dimension is the stride (in elements) to the beginning of next group of 32-columns. E.g. if matrix has 33
|
442 |
+
* columns and 2 rows, ld must be at least (32) * 2 = 64.
|
443 |
+
*/
|
444 |
+
CUBLASLT_ORDER_COL32 = 2,
|
445 |
+
/** Column-major ordered tiles of composite tiles with total 32 columns and 8 rows, tile composed of interleaved
|
446 |
+
* inner tiles of 4 columns within 4 even or odd rows in an alternating pattern.
|
447 |
+
*
|
448 |
+
* Leading dimension is the stride (in elements) to the beginning of the first 32 column x 8 row tile for the next
|
449 |
+
* 32-wide group of columns. E.g. if matrix has 33 columns and 1 row, ld must be at least (32 * 8) * 1 = 256.
|
450 |
+
*/
|
451 |
+
CUBLASLT_ORDER_COL4_4R2_8C = 3,
|
452 |
+
/** Column-major ordered tiles of composite tiles with total 32 columns ands 32 rows.
|
453 |
+
* Element offset within the tile is calculated as (((row%8)/2*4+row/8)*2+row%2)*32+col.
|
454 |
+
*
|
455 |
+
* Leading dimension is the stride (in elements) to the beginning of the first 32 column x 32 row tile for the next
|
456 |
+
* 32-wide group of columns. E.g. if matrix has 33 columns and 1 row, ld must be at least (32*32)*1 = 1024.
|
457 |
+
*/
|
458 |
+
CUBLASLT_ORDER_COL32_2R_4R4 = 4,
|
459 |
+
|
460 |
+
} cublasLtOrder_t;
|
461 |
+
|
462 |
+
/** Attributes of memory layout */
|
463 |
+
typedef enum {
|
464 |
+
/** Data type, see cudaDataType.
|
465 |
+
*
|
466 |
+
* uint32_t
|
467 |
+
*/
|
468 |
+
CUBLASLT_MATRIX_LAYOUT_TYPE = 0,
|
469 |
+
|
470 |
+
/** Memory order of the data, see cublasLtOrder_t.
|
471 |
+
*
|
472 |
+
* int32_t, default: CUBLASLT_ORDER_COL
|
473 |
+
*/
|
474 |
+
CUBLASLT_MATRIX_LAYOUT_ORDER = 1,
|
475 |
+
|
476 |
+
/** Number of rows.
|
477 |
+
*
|
478 |
+
* Usually only values that can be expressed as int32_t are supported.
|
479 |
+
*
|
480 |
+
* uint64_t
|
481 |
+
*/
|
482 |
+
CUBLASLT_MATRIX_LAYOUT_ROWS = 2,
|
483 |
+
|
484 |
+
/** Number of columns.
|
485 |
+
*
|
486 |
+
* Usually only values that can be expressed as int32_t are supported.
|
487 |
+
*
|
488 |
+
* uint64_t
|
489 |
+
*/
|
490 |
+
CUBLASLT_MATRIX_LAYOUT_COLS = 3,
|
491 |
+
|
492 |
+
/** Matrix leading dimension.
|
493 |
+
*
|
494 |
+
* For CUBLASLT_ORDER_COL this is stride (in elements) of matrix column, for more details and documentation for
|
495 |
+
* other memory orders see documentation for cublasLtOrder_t values.
|
496 |
+
*
|
497 |
+
* Currently only non-negative values are supported, must be large enough so that matrix memory locations are not
|
498 |
+
* overlapping (e.g. greater or equal to CUBLASLT_MATRIX_LAYOUT_ROWS in case of CUBLASLT_ORDER_COL).
|
499 |
+
*
|
500 |
+
* int64_t;
|
501 |
+
*/
|
502 |
+
CUBLASLT_MATRIX_LAYOUT_LD = 4,
|
503 |
+
|
504 |
+
/** Number of matmul operations to perform in the batch.
|
505 |
+
*
|
506 |
+
* See also CUBLASLT_ALGO_CAP_STRIDED_BATCH_SUPPORT
|
507 |
+
*
|
508 |
+
* int32_t, default: 1
|
509 |
+
*/
|
510 |
+
CUBLASLT_MATRIX_LAYOUT_BATCH_COUNT = 5,
|
511 |
+
|
512 |
+
/** Stride (in elements) to the next matrix for strided batch operation.
|
513 |
+
*
|
514 |
+
* When matrix type is planar-complex (CUBLASLT_MATRIX_LAYOUT_PLANE_OFFSET != 0), batch stride
|
515 |
+
* is interpreted by cublasLtMatmul() in number of real valued sub-elements. E.g. for data of type CUDA_C_16F,
|
516 |
+
* offset of 1024B is encoded as a stride of value 512 (since each element of the real and imaginary matrices
|
517 |
+
* is a 2B (16bit) floating point type).
|
518 |
+
*
|
519 |
+
* NOTE: A bug in cublasLtMatrixTransform() causes it to interpret the batch stride for a planar-complex matrix
|
520 |
+
* as if it was specified in number of complex elements. Therefore an offset of 1024B must be encoded as stride
|
521 |
+
* value 256 when calling cublasLtMatrixTransform() (each complex element is 4B with real and imaginary values 2B
|
522 |
+
* each). This behavior is expected to be corrected in the next major cuBLAS version.
|
523 |
+
*
|
524 |
+
* int64_t, default: 0
|
525 |
+
*/
|
526 |
+
CUBLASLT_MATRIX_LAYOUT_STRIDED_BATCH_OFFSET = 6,
|
527 |
+
|
528 |
+
/** Stride (in bytes) to the imaginary plane for planar complex layout.
|
529 |
+
*
|
530 |
+
* int64_t, default: 0 - 0 means that layout is regular (real and imaginary parts of complex numbers are interleaved
|
531 |
+
* in memory in each element)
|
532 |
+
*/
|
533 |
+
CUBLASLT_MATRIX_LAYOUT_PLANE_OFFSET = 7,
|
534 |
+
} cublasLtMatrixLayoutAttribute_t;
|
535 |
+
|
536 |
+
/** Internal. Do not use directly.
|
537 |
+
*/
|
538 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixLayoutInit_internal( //
|
539 |
+
cublasLtMatrixLayout_t matLayout,
|
540 |
+
size_t size,
|
541 |
+
cudaDataType type,
|
542 |
+
uint64_t rows,
|
543 |
+
uint64_t cols,
|
544 |
+
int64_t ld);
|
545 |
+
|
546 |
+
/** Initialize matrix layout descriptor in pre-allocated space.
|
547 |
+
*
|
548 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if size of the pre-allocated space is insufficient
|
549 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
550 |
+
*/
|
551 |
+
static inline cublasStatus_t cublasLtMatrixLayoutInit(
|
552 |
+
cublasLtMatrixLayout_t matLayout, cudaDataType type, uint64_t rows, uint64_t cols, int64_t ld) {
|
553 |
+
return cublasLtMatrixLayoutInit_internal(matLayout, sizeof(*matLayout), type, rows, cols, ld);
|
554 |
+
}
|
555 |
+
|
556 |
+
/** Create new matrix layout descriptor.
|
557 |
+
*
|
558 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if memory could not be allocated
|
559 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
560 |
+
*/
|
561 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixLayoutCreate( //
|
562 |
+
cublasLtMatrixLayout_t* matLayout,
|
563 |
+
cudaDataType type,
|
564 |
+
uint64_t rows,
|
565 |
+
uint64_t cols,
|
566 |
+
int64_t ld);
|
567 |
+
|
568 |
+
/** Destroy matrix layout descriptor.
|
569 |
+
*
|
570 |
+
* \retval CUBLAS_STATUS_SUCCESS if operation was successful
|
571 |
+
*/
|
572 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixLayoutDestroy(cublasLtMatrixLayout_t matLayout);
|
573 |
+
|
574 |
+
/** Set matrix layout descriptor attribute.
|
575 |
+
*
|
576 |
+
* \param[in] matLayout The descriptor
|
577 |
+
* \param[in] attr The attribute
|
578 |
+
* \param[in] buf memory address containing the new value
|
579 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
580 |
+
*
|
581 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if buf is NULL or sizeInBytes doesn't match size of internal storage for
|
582 |
+
* selected attribute
|
583 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute was set successfully
|
584 |
+
*/
|
585 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixLayoutSetAttribute( //
|
586 |
+
cublasLtMatrixLayout_t matLayout,
|
587 |
+
cublasLtMatrixLayoutAttribute_t attr,
|
588 |
+
const void* buf,
|
589 |
+
size_t sizeInBytes);
|
590 |
+
|
591 |
+
/** Get matrix layout descriptor attribute.
|
592 |
+
*
|
593 |
+
* \param[in] matLayout The descriptor
|
594 |
+
* \param[in] attr The attribute
|
595 |
+
* \param[out] buf memory address containing the new value
|
596 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
597 |
+
* \param[out] sizeWritten only valid when return value is CUBLAS_STATUS_SUCCESS. If sizeInBytes is non-zero: number of
|
598 |
+
* bytes actually written, if sizeInBytes is 0: number of bytes needed to write full contents
|
599 |
+
*
|
600 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if sizeInBytes is 0 and sizeWritten is NULL, or if sizeInBytes is non-zero
|
601 |
+
* and buf is NULL or sizeInBytes doesn't match size of internal storage for
|
602 |
+
* selected attribute
|
603 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute's value was successfully written to user memory
|
604 |
+
*/
|
605 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixLayoutGetAttribute( //
|
606 |
+
cublasLtMatrixLayout_t matLayout,
|
607 |
+
cublasLtMatrixLayoutAttribute_t attr,
|
608 |
+
void* buf,
|
609 |
+
size_t sizeInBytes,
|
610 |
+
size_t* sizeWritten);
|
611 |
+
|
612 |
+
/* ---------------------------------------------------------------------------------------*/
|
613 |
+
/* Helper functions for cublasLtMatmulDesc_t */
|
614 |
+
/* ---------------------------------------------------------------------------------------*/
|
615 |
+
|
616 |
+
/** Matmul descriptor attributes to define details of the operation. */
|
617 |
+
typedef enum {
|
618 |
+
/** Compute type, see cudaDataType. Defines data type used for multiply and accumulate operations and the
|
619 |
+
* accumulator during matrix multiplication.
|
620 |
+
*
|
621 |
+
* int32_t
|
622 |
+
*/
|
623 |
+
CUBLASLT_MATMUL_DESC_COMPUTE_TYPE = 0,
|
624 |
+
|
625 |
+
/** Scale type, see cudaDataType. Defines data type of alpha and beta. Accumulator and value from matrix C are
|
626 |
+
* typically converted to scale type before final scaling. Value is then converted from scale type to type of matrix
|
627 |
+
* D before being stored in memory.
|
628 |
+
*
|
629 |
+
* int32_t, default: same as CUBLASLT_MATMUL_DESC_COMPUTE_TYPE
|
630 |
+
*/
|
631 |
+
CUBLASLT_MATMUL_DESC_SCALE_TYPE = 1,
|
632 |
+
|
633 |
+
/** Pointer mode of alpha and beta, see cublasLtPointerMode_t. When CUBLASLT_POINTER_MODE_DEVICE_VECTOR is in use,
|
634 |
+
* alpha/beta vector lenghts must match number of output matrix rows.
|
635 |
+
*
|
636 |
+
* int32_t, default: CUBLASLT_POINTER_MODE_HOST
|
637 |
+
*/
|
638 |
+
CUBLASLT_MATMUL_DESC_POINTER_MODE = 2,
|
639 |
+
|
640 |
+
/** Transform of matrix A, see cublasOperation_t.
|
641 |
+
*
|
642 |
+
* int32_t, default: CUBLAS_OP_N
|
643 |
+
*/
|
644 |
+
CUBLASLT_MATMUL_DESC_TRANSA = 3,
|
645 |
+
|
646 |
+
/** Transform of matrix B, see cublasOperation_t.
|
647 |
+
*
|
648 |
+
* int32_t, default: CUBLAS_OP_N
|
649 |
+
*/
|
650 |
+
CUBLASLT_MATMUL_DESC_TRANSB = 4,
|
651 |
+
|
652 |
+
/** Transform of matrix C, see cublasOperation_t.
|
653 |
+
*
|
654 |
+
* Currently only CUBLAS_OP_N is supported.
|
655 |
+
*
|
656 |
+
* int32_t, default: CUBLAS_OP_N
|
657 |
+
*/
|
658 |
+
CUBLASLT_MATMUL_DESC_TRANSC = 5,
|
659 |
+
|
660 |
+
/** Matrix fill mode, see cublasFillMode_t.
|
661 |
+
*
|
662 |
+
* int32_t, default: CUBLAS_FILL_MODE_FULL
|
663 |
+
*/
|
664 |
+
CUBLASLT_MATMUL_DESC_FILL_MODE = 6,
|
665 |
+
|
666 |
+
/** Epilogue function, see cublasLtEpilogue_t.
|
667 |
+
*
|
668 |
+
* uint32_t, default: CUBLASLT_EPILOGUE_DEFAULT
|
669 |
+
*/
|
670 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE = 7,
|
671 |
+
|
672 |
+
/** Bias or bias gradient vector pointer in the device memory.
|
673 |
+
*
|
674 |
+
* Bias case. See CUBLASLT_EPILOGUE_BIAS.
|
675 |
+
* For bias data type see CUBLASLT_MATMUL_DESC_BIAS_DATA_TYPE.
|
676 |
+
*
|
677 |
+
* Bias vector length must match matrix D rows count.
|
678 |
+
*
|
679 |
+
* Bias gradient case. See CUBLASLT_EPILOGUE_DRELU_BGRAD and CUBLASLT_EPILOGUE_DGELU_BGRAD.
|
680 |
+
* Bias gradient vector elements are the same type as the output elements
|
681 |
+
* (Ctype) with the exception of IMMA kernels (see above).
|
682 |
+
*
|
683 |
+
* Routines that don't dereference this pointer, like cublasLtMatmulAlgoGetHeuristic()
|
684 |
+
* depend on its value to determine expected pointer alignment.
|
685 |
+
*
|
686 |
+
* Bias case: const void *, default: NULL
|
687 |
+
* Bias gradient case: void *, default: NULL
|
688 |
+
*/
|
689 |
+
CUBLASLT_MATMUL_DESC_BIAS_POINTER = 8,
|
690 |
+
|
691 |
+
/** Batch stride for bias or bias gradient vector.
|
692 |
+
*
|
693 |
+
* Used together with CUBLASLT_MATMUL_DESC_BIAS_POINTER when matrix D's CUBLASLT_MATRIX_LAYOUT_BATCH_COUNT > 1.
|
694 |
+
*
|
695 |
+
* int64_t, default: 0
|
696 |
+
*/
|
697 |
+
CUBLASLT_MATMUL_DESC_BIAS_BATCH_STRIDE = 10,
|
698 |
+
|
699 |
+
/** Pointer for epilogue auxiliary buffer.
|
700 |
+
*
|
701 |
+
* - Output vector for ReLu bit-mask in forward pass when CUBLASLT_EPILOGUE_RELU_AUX
|
702 |
+
* or CUBLASLT_EPILOGUE_RELU_AUX_BIAS epilogue is used.
|
703 |
+
* - Input vector for ReLu bit-mask in backward pass when
|
704 |
+
* CUBLASLT_EPILOGUE_DRELU_BGRAD epilogue is used.
|
705 |
+
*
|
706 |
+
* - Output of GELU input matrix in forward pass when
|
707 |
+
* CUBLASLT_EPILOGUE_GELU_AUX_BIAS epilogue is used.
|
708 |
+
* - Input of GELU input matrix for backward pass when
|
709 |
+
* CUBLASLT_EPILOGUE_DGELU_BGRAD epilogue is used.
|
710 |
+
*
|
711 |
+
* For aux data type see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_DATA_TYPE.
|
712 |
+
*
|
713 |
+
* Routines that don't dereference this pointer, like cublasLtMatmulAlgoGetHeuristic()
|
714 |
+
* depend on its value to determine expected pointer alignment.
|
715 |
+
*
|
716 |
+
* Requires setting CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_LD attribute.
|
717 |
+
*
|
718 |
+
* Forward pass: void *, default: NULL
|
719 |
+
* Backward pass: const void *, default: NULL
|
720 |
+
*/
|
721 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER = 11,
|
722 |
+
|
723 |
+
/** Leading dimension for epilogue auxiliary buffer.
|
724 |
+
*
|
725 |
+
* - ReLu bit-mask matrix leading dimension in elements (i.e. bits)
|
726 |
+
* when CUBLASLT_EPILOGUE_RELU_AUX, CUBLASLT_EPILOGUE_RELU_AUX_BIAS or CUBLASLT_EPILOGUE_DRELU_BGRAD epilogue is
|
727 |
+
* used. Must be divisible by 128 and be no less than the number of rows in the output matrix.
|
728 |
+
*
|
729 |
+
* - GELU input matrix leading dimension in elements
|
730 |
+
* when CUBLASLT_EPILOGUE_GELU_AUX_BIAS or CUBLASLT_EPILOGUE_DGELU_BGRAD epilogue used.
|
731 |
+
* Must be divisible by 8 and be no less than the number of rows in the output matrix.
|
732 |
+
*
|
733 |
+
* int64_t, default: 0
|
734 |
+
*/
|
735 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_LD = 12,
|
736 |
+
|
737 |
+
/** Batch stride for epilogue auxiliary buffer.
|
738 |
+
*
|
739 |
+
* - ReLu bit-mask matrix batch stride in elements (i.e. bits)
|
740 |
+
* when CUBLASLT_EPILOGUE_RELU_AUX, CUBLASLT_EPILOGUE_RELU_AUX_BIAS or CUBLASLT_EPILOGUE_DRELU_BGRAD epilogue is
|
741 |
+
* used. Must be divisible by 128.
|
742 |
+
*
|
743 |
+
* - GELU input matrix batch stride in elements
|
744 |
+
* when CUBLASLT_EPILOGUE_GELU_AUX_BIAS or CUBLASLT_EPILOGUE_DGELU_BGRAD epilogue used.
|
745 |
+
* Must be divisible by 8.
|
746 |
+
*
|
747 |
+
* int64_t, default: 0
|
748 |
+
*/
|
749 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_BATCH_STRIDE = 13,
|
750 |
+
|
751 |
+
/** Batch stride for alpha vector.
|
752 |
+
*
|
753 |
+
* Used together with CUBLASLT_POINTER_MODE_ALPHA_DEVICE_VECTOR_BETA_HOST when matrix D's
|
754 |
+
* CUBLASLT_MATRIX_LAYOUT_BATCH_COUNT > 1. If CUBLASLT_POINTER_MODE_ALPHA_DEVICE_VECTOR_BETA_ZERO is set then
|
755 |
+
* CUBLASLT_MATMUL_DESC_ALPHA_VECTOR_BATCH_STRIDE must be set to 0 as this mode doesnt supported batched alpha vector.
|
756 |
+
*
|
757 |
+
* int64_t, default: 0
|
758 |
+
*/
|
759 |
+
CUBLASLT_MATMUL_DESC_ALPHA_VECTOR_BATCH_STRIDE = 14,
|
760 |
+
|
761 |
+
/** Number of SMs to target for parallel execution. Optimizes heuristics for execution on a different number of SMs
|
762 |
+
* when user expects a concurrent stream to be using some of the device resources.
|
763 |
+
*
|
764 |
+
* int32_t, default: 0 - use the number reported by the device.
|
765 |
+
*/
|
766 |
+
CUBLASLT_MATMUL_DESC_SM_COUNT_TARGET = 15,
|
767 |
+
|
768 |
+
/** Device pointer to the scale factor value that converts data in matrix A to the compute data type range.
|
769 |
+
*
|
770 |
+
* The scaling factor value must have the same type as the compute type.
|
771 |
+
*
|
772 |
+
* If not specified, or set to NULL, the scaling factor is assumed to be 1.
|
773 |
+
*
|
774 |
+
* If set for an unsupported matrix data, scale, and compute type combination, calling cublasLtMatmul()
|
775 |
+
* will return CUBLAS_INVALID_VALUE.
|
776 |
+
*
|
777 |
+
* const void *, default: NULL
|
778 |
+
*/
|
779 |
+
CUBLASLT_MATMUL_DESC_A_SCALE_POINTER = 17,
|
780 |
+
|
781 |
+
/** Device pointer to the scale factor value to convert data in matrix B to compute data type range.
|
782 |
+
*
|
783 |
+
* The scaling factor value must have the same type as the compute type.
|
784 |
+
*
|
785 |
+
* If not specified, or set to NULL, the scaling factor is assumed to be 1.
|
786 |
+
*
|
787 |
+
* If set for an unsupported matrix data, scale, and compute type combination, calling cublasLtMatmul()
|
788 |
+
* will return CUBLAS_INVALID_VALUE.
|
789 |
+
*
|
790 |
+
* const void *, default: NULL
|
791 |
+
*/
|
792 |
+
CUBLASLT_MATMUL_DESC_B_SCALE_POINTER = 18,
|
793 |
+
|
794 |
+
/** Device pointer to the scale factor value to convert data in matrix C to compute data type range.
|
795 |
+
*
|
796 |
+
* The scaling factor value must have the same type as the compute type.
|
797 |
+
*
|
798 |
+
* If not specified, or set to NULL, the scaling factor is assumed to be 1.
|
799 |
+
*
|
800 |
+
* If set for an unsupported matrix data, scale, and compute type combination, calling cublasLtMatmul()
|
801 |
+
* will return CUBLAS_INVALID_VALUE.
|
802 |
+
*
|
803 |
+
* const void *, default: NULL
|
804 |
+
*/
|
805 |
+
CUBLASLT_MATMUL_DESC_C_SCALE_POINTER = 19,
|
806 |
+
|
807 |
+
/** Device pointer to the scale factor value to convert data in matrix D to compute data type range.
|
808 |
+
*
|
809 |
+
* The scaling factor value must have the same type as the compute type.
|
810 |
+
*
|
811 |
+
* If not specified, or set to NULL, the scaling factor is assumed to be 1.
|
812 |
+
*
|
813 |
+
* If set for an unsupported matrix data, scale, and compute type combination, calling cublasLtMatmul()
|
814 |
+
* will return CUBLAS_INVALID_VALUE.
|
815 |
+
*
|
816 |
+
* const void *, default: NULL
|
817 |
+
*/
|
818 |
+
CUBLASLT_MATMUL_DESC_D_SCALE_POINTER = 20,
|
819 |
+
|
820 |
+
/** Device pointer to the memory location that on completion will be set to the maximum of absolute values in the
|
821 |
+
* output matrix.
|
822 |
+
*
|
823 |
+
* The computed value has the same type as the compute type.
|
824 |
+
*
|
825 |
+
* If not specified or set to NULL, the maximum absolute value is not computed. If set for an unsupported matrix
|
826 |
+
* data, scale, and compute type combination, calling cublasLtMatmul() will return CUBLAS_INVALID_VALUE.
|
827 |
+
*
|
828 |
+
* void *, default: NULL
|
829 |
+
*/
|
830 |
+
CUBLASLT_MATMUL_DESC_AMAX_D_POINTER = 21,
|
831 |
+
|
832 |
+
/** Type of the data to be stored to the memory pointed to by CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
833 |
+
*
|
834 |
+
* If unset, the data type defaults to the type of elements of the output matrix with some exceptions, see details
|
835 |
+
* below.
|
836 |
+
*
|
837 |
+
* ReLu uses a bit-mask.
|
838 |
+
*
|
839 |
+
* GELU input matrix elements type is the same as the type of elements of
|
840 |
+
* the output matrix with some exceptions, see details below.
|
841 |
+
*
|
842 |
+
* For fp8 kernels with output type CUDA_R_8F_E4M3 the aux data type can be CUDA_R_8F_E4M3 or CUDA_R_16F with some
|
843 |
+
* restrictions. See https://docs.nvidia.com/cuda/cublas/index.html#cublasLtMatmulDescAttributes_t for more details.
|
844 |
+
*
|
845 |
+
* If set for an unsupported matrix data, scale, and compute type combination, calling cublasLtMatmul()
|
846 |
+
* will return CUBLAS_INVALID_VALUE.
|
847 |
+
*
|
848 |
+
* int32_t based on cudaDataType, default: -1
|
849 |
+
*/
|
850 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_DATA_TYPE = 22,
|
851 |
+
|
852 |
+
/** Device pointer to the scaling factor value to convert results from compute type data range to storage
|
853 |
+
* data range in the auxiliary matrix that is set via CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
854 |
+
*
|
855 |
+
* The scaling factor value must have the same type as the compute type.
|
856 |
+
*
|
857 |
+
* If not specified, or set to NULL, the scaling factor is assumed to be 1. If set for an unsupported matrix data,
|
858 |
+
* scale, and compute type combination, calling cublasLtMatmul() will return CUBLAS_INVALID_VALUE.
|
859 |
+
*
|
860 |
+
* void *, default: NULL
|
861 |
+
*/
|
862 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_SCALE_POINTER = 23,
|
863 |
+
|
864 |
+
/** Device pointer to the memory location that on completion will be set to the maximum of absolute values in the
|
865 |
+
* buffer that is set via CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
866 |
+
*
|
867 |
+
* The computed value has the same type as the compute type.
|
868 |
+
*
|
869 |
+
* If not specified or set to NULL, the maximum absolute value is not computed. If set for an unsupported matrix
|
870 |
+
* data, scale, and compute type combination, calling cublasLtMatmul() will return CUBLAS_INVALID_VALUE.
|
871 |
+
*
|
872 |
+
* void *, default: NULL
|
873 |
+
*/
|
874 |
+
CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_AMAX_POINTER = 24,
|
875 |
+
|
876 |
+
/** Flag for managing fp8 fast accumulation mode.
|
877 |
+
* When enabled, problem execution might be faster but at the cost of lower accuracy because intermediate results
|
878 |
+
* will not periodically be promoted to a higher precision.
|
879 |
+
*
|
880 |
+
* int8_t, default: 0 - fast accumulation mode is disabled.
|
881 |
+
*/
|
882 |
+
CUBLASLT_MATMUL_DESC_FAST_ACCUM = 25,
|
883 |
+
|
884 |
+
/** Type of bias or bias gradient vector in the device memory.
|
885 |
+
*
|
886 |
+
* Bias case: see CUBLASLT_EPILOGUE_BIAS.
|
887 |
+
*
|
888 |
+
* Bias vector elements are the same type as the elements of output matrix (Dtype) with the following exceptions:
|
889 |
+
* - IMMA kernels with computeType=CUDA_R_32I and Ctype=CUDA_R_8I where the bias vector elements
|
890 |
+
* are the same type as alpha, beta (CUBLASLT_MATMUL_DESC_SCALE_TYPE=CUDA_R_32F)
|
891 |
+
* - fp8 kernels with an output type of CUDA_R_32F, CUDA_R_8F_E4M3 or CUDA_R_8F_E5M2, See
|
892 |
+
* https://docs.nvidia.com/cuda/cublas/index.html#cublasLtMatmul for details.
|
893 |
+
*
|
894 |
+
* int32_t based on cudaDataType, default: -1
|
895 |
+
*/
|
896 |
+
CUBLASLT_MATMUL_DESC_BIAS_DATA_TYPE = 26,
|
897 |
+
} cublasLtMatmulDescAttributes_t;
|
898 |
+
|
899 |
+
/** Internal. Do not use directly.
|
900 |
+
*/
|
901 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulDescInit_internal( //
|
902 |
+
cublasLtMatmulDesc_t matmulDesc,
|
903 |
+
size_t size,
|
904 |
+
cublasComputeType_t computeType,
|
905 |
+
cudaDataType_t scaleType);
|
906 |
+
|
907 |
+
/** Initialize matmul operation descriptor in pre-allocated space.
|
908 |
+
*
|
909 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if size of the pre-allocated space is insufficient
|
910 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was initialized successfully
|
911 |
+
*/
|
912 |
+
static inline cublasStatus_t cublasLtMatmulDescInit( //
|
913 |
+
cublasLtMatmulDesc_t matmulDesc,
|
914 |
+
cublasComputeType_t computeType,
|
915 |
+
cudaDataType_t scaleType) {
|
916 |
+
return cublasLtMatmulDescInit_internal(matmulDesc, sizeof(*matmulDesc), computeType, scaleType);
|
917 |
+
}
|
918 |
+
|
919 |
+
/** Create new matmul operation descriptor.
|
920 |
+
*
|
921 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if memory could not be allocated
|
922 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
923 |
+
*/
|
924 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulDescCreate(cublasLtMatmulDesc_t* matmulDesc,
|
925 |
+
cublasComputeType_t computeType,
|
926 |
+
cudaDataType_t scaleType);
|
927 |
+
|
928 |
+
/** Destroy matmul operation descriptor.
|
929 |
+
*
|
930 |
+
* \retval CUBLAS_STATUS_SUCCESS if operation was successful
|
931 |
+
*/
|
932 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulDescDestroy(cublasLtMatmulDesc_t matmulDesc);
|
933 |
+
|
934 |
+
/** Set matmul operation descriptor attribute.
|
935 |
+
*
|
936 |
+
* \param[in] matmulDesc The descriptor
|
937 |
+
* \param[in] attr The attribute
|
938 |
+
* \param[in] buf memory address containing the new value
|
939 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
940 |
+
*
|
941 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if buf is NULL or sizeInBytes doesn't match size of internal storage for
|
942 |
+
* selected attribute
|
943 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute was set successfully
|
944 |
+
*/
|
945 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulDescSetAttribute( //
|
946 |
+
cublasLtMatmulDesc_t matmulDesc,
|
947 |
+
cublasLtMatmulDescAttributes_t attr,
|
948 |
+
const void* buf,
|
949 |
+
size_t sizeInBytes);
|
950 |
+
|
951 |
+
/** Get matmul operation descriptor attribute.
|
952 |
+
*
|
953 |
+
* \param[in] matmulDesc The descriptor
|
954 |
+
* \param[in] attr The attribute
|
955 |
+
* \param[out] buf memory address containing the new value
|
956 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
957 |
+
* \param[out] sizeWritten only valid when return value is CUBLAS_STATUS_SUCCESS. If sizeInBytes is non-zero: number of
|
958 |
+
* bytes actually written, if sizeInBytes is 0: number of bytes needed to write full contents
|
959 |
+
*
|
960 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if sizeInBytes is 0 and sizeWritten is NULL, or if sizeInBytes is non-zero
|
961 |
+
* and buf is NULL or sizeInBytes doesn't match size of internal storage for
|
962 |
+
* selected attribute
|
963 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute's value was successfully written to user memory
|
964 |
+
*/
|
965 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulDescGetAttribute( //
|
966 |
+
cublasLtMatmulDesc_t matmulDesc,
|
967 |
+
cublasLtMatmulDescAttributes_t attr,
|
968 |
+
void* buf,
|
969 |
+
size_t sizeInBytes,
|
970 |
+
size_t* sizeWritten);
|
971 |
+
|
972 |
+
/* ---------------------------------------------------------------------------------------*/
|
973 |
+
/* Helper functions for cublasLtMatrixTransformDesc_t */
|
974 |
+
/* ---------------------------------------------------------------------------------------*/
|
975 |
+
|
976 |
+
/** Matrix transform descriptor attributes to define details of the operation.
|
977 |
+
*/
|
978 |
+
typedef enum {
|
979 |
+
/** Scale type, see cudaDataType. Inputs are converted to scale type for scaling and summation and results are then
|
980 |
+
* converted to output type to store in memory.
|
981 |
+
*
|
982 |
+
* int32_t
|
983 |
+
*/
|
984 |
+
CUBLASLT_MATRIX_TRANSFORM_DESC_SCALE_TYPE,
|
985 |
+
|
986 |
+
/** Pointer mode of alpha and beta, see cublasLtPointerMode_t.
|
987 |
+
*
|
988 |
+
* int32_t, default: CUBLASLT_POINTER_MODE_HOST
|
989 |
+
*/
|
990 |
+
CUBLASLT_MATRIX_TRANSFORM_DESC_POINTER_MODE,
|
991 |
+
|
992 |
+
/** Transform of matrix A, see cublasOperation_t.
|
993 |
+
*
|
994 |
+
* int32_t, default: CUBLAS_OP_N
|
995 |
+
*/
|
996 |
+
CUBLASLT_MATRIX_TRANSFORM_DESC_TRANSA,
|
997 |
+
|
998 |
+
/** Transform of matrix B, see cublasOperation_t.
|
999 |
+
*
|
1000 |
+
* int32_t, default: CUBLAS_OP_N
|
1001 |
+
*/
|
1002 |
+
CUBLASLT_MATRIX_TRANSFORM_DESC_TRANSB,
|
1003 |
+
} cublasLtMatrixTransformDescAttributes_t;
|
1004 |
+
|
1005 |
+
/** Internal. Do not use directly.
|
1006 |
+
*/
|
1007 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixTransformDescInit_internal(cublasLtMatrixTransformDesc_t transformDesc,
|
1008 |
+
size_t size,
|
1009 |
+
cudaDataType scaleType);
|
1010 |
+
|
1011 |
+
/** Initialize matrix transform operation descriptor in pre-allocated space.
|
1012 |
+
*
|
1013 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if size of the pre-allocated space is insufficient
|
1014 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
1015 |
+
*/
|
1016 |
+
static inline cublasStatus_t cublasLtMatrixTransformDescInit(cublasLtMatrixTransformDesc_t transformDesc,
|
1017 |
+
cudaDataType scaleType) {
|
1018 |
+
return cublasLtMatrixTransformDescInit_internal(transformDesc, sizeof(*transformDesc), scaleType);
|
1019 |
+
}
|
1020 |
+
|
1021 |
+
/** Create new matrix transform operation descriptor.
|
1022 |
+
*
|
1023 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if memory could not be allocated
|
1024 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
1025 |
+
*/
|
1026 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixTransformDescCreate(cublasLtMatrixTransformDesc_t* transformDesc,
|
1027 |
+
cudaDataType scaleType);
|
1028 |
+
|
1029 |
+
/** Destroy matrix transform operation descriptor.
|
1030 |
+
*
|
1031 |
+
* \retval CUBLAS_STATUS_SUCCESS if operation was successful
|
1032 |
+
*/
|
1033 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixTransformDescDestroy(cublasLtMatrixTransformDesc_t transformDesc);
|
1034 |
+
|
1035 |
+
/** Set matrix transform operation descriptor attribute.
|
1036 |
+
*
|
1037 |
+
* \param[in] transformDesc The descriptor
|
1038 |
+
* \param[in] attr The attribute
|
1039 |
+
* \param[in] buf memory address containing the new value
|
1040 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1041 |
+
*
|
1042 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1043 |
+
* selected attribute
|
1044 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute was set successfully
|
1045 |
+
*/
|
1046 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixTransformDescSetAttribute( //
|
1047 |
+
cublasLtMatrixTransformDesc_t transformDesc,
|
1048 |
+
cublasLtMatrixTransformDescAttributes_t attr,
|
1049 |
+
const void* buf,
|
1050 |
+
size_t sizeInBytes);
|
1051 |
+
|
1052 |
+
/** Get matrix transform operation descriptor attribute.
|
1053 |
+
*
|
1054 |
+
* \param[in] transformDesc The descriptor
|
1055 |
+
* \param[in] attr The attribute
|
1056 |
+
* \param[out] buf memory address containing the new value
|
1057 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1058 |
+
* \param[out] sizeWritten only valid when return value is CUBLAS_STATUS_SUCCESS. If sizeInBytes is non-zero: number
|
1059 |
+
* of bytes actually written, if sizeInBytes is 0: number of bytes needed to write full contents
|
1060 |
+
*
|
1061 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if sizeInBytes is 0 and sizeWritten is NULL, or if sizeInBytes is non-zero
|
1062 |
+
* and buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1063 |
+
* selected attribute
|
1064 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute's value was successfully written to user memory
|
1065 |
+
*/
|
1066 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatrixTransformDescGetAttribute( //
|
1067 |
+
cublasLtMatrixTransformDesc_t transformDesc,
|
1068 |
+
cublasLtMatrixTransformDescAttributes_t attr,
|
1069 |
+
void* buf,
|
1070 |
+
size_t sizeInBytes,
|
1071 |
+
size_t* sizeWritten);
|
1072 |
+
|
1073 |
+
/** Reduction scheme for portions of the dot-product calculated in parallel (a. k. a. "split - K").
|
1074 |
+
*/
|
1075 |
+
typedef enum {
|
1076 |
+
/** No reduction scheme, dot-product shall be performed in one sequence.
|
1077 |
+
*/
|
1078 |
+
CUBLASLT_REDUCTION_SCHEME_NONE = 0,
|
1079 |
+
|
1080 |
+
/** Reduction is performed "in place" - using the output buffer (and output data type) and counters (in workspace) to
|
1081 |
+
* guarantee the sequentiality.
|
1082 |
+
*/
|
1083 |
+
CUBLASLT_REDUCTION_SCHEME_INPLACE = 1,
|
1084 |
+
|
1085 |
+
/** Intermediate results are stored in compute type in the workspace and reduced in a separate step.
|
1086 |
+
*/
|
1087 |
+
CUBLASLT_REDUCTION_SCHEME_COMPUTE_TYPE = 2,
|
1088 |
+
|
1089 |
+
/** Intermediate results are stored in output type in the workspace and reduced in a separate step.
|
1090 |
+
*/
|
1091 |
+
CUBLASLT_REDUCTION_SCHEME_OUTPUT_TYPE = 4,
|
1092 |
+
|
1093 |
+
CUBLASLT_REDUCTION_SCHEME_MASK = 0x7,
|
1094 |
+
} cublasLtReductionScheme_t;
|
1095 |
+
|
1096 |
+
/** Postprocessing options for the epilogue
|
1097 |
+
*/
|
1098 |
+
typedef enum {
|
1099 |
+
/** No special postprocessing, just scale and quantize results if necessary.
|
1100 |
+
*/
|
1101 |
+
CUBLASLT_EPILOGUE_DEFAULT = 1,
|
1102 |
+
|
1103 |
+
/** ReLu, apply ReLu point-wise transform to the results (x:=max(x, 0)).
|
1104 |
+
*/
|
1105 |
+
CUBLASLT_EPILOGUE_RELU = 2,
|
1106 |
+
|
1107 |
+
/** ReLu, apply ReLu point-wise transform to the results (x:=max(x, 0)).
|
1108 |
+
*
|
1109 |
+
* This epilogue mode produces an extra output, a ReLu bit-mask matrix,
|
1110 |
+
* see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1111 |
+
*/
|
1112 |
+
CUBLASLT_EPILOGUE_RELU_AUX = (CUBLASLT_EPILOGUE_RELU | 128),
|
1113 |
+
|
1114 |
+
/** Bias, apply (broadcasted) Bias from bias vector. Bias vector length must match matrix D rows, it must be packed
|
1115 |
+
* (stride between vector elements is 1). Bias vector is broadcasted to all columns and added before applying final
|
1116 |
+
* postprocessing.
|
1117 |
+
*/
|
1118 |
+
CUBLASLT_EPILOGUE_BIAS = 4,
|
1119 |
+
|
1120 |
+
/** ReLu and Bias, apply Bias and then ReLu transform
|
1121 |
+
*/
|
1122 |
+
CUBLASLT_EPILOGUE_RELU_BIAS = (CUBLASLT_EPILOGUE_RELU | CUBLASLT_EPILOGUE_BIAS),
|
1123 |
+
|
1124 |
+
/** ReLu and Bias, apply Bias and then ReLu transform
|
1125 |
+
*
|
1126 |
+
* This epilogue mode produces an extra output, a ReLu bit-mask matrix,
|
1127 |
+
* see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1128 |
+
*/
|
1129 |
+
CUBLASLT_EPILOGUE_RELU_AUX_BIAS = (CUBLASLT_EPILOGUE_RELU_AUX | CUBLASLT_EPILOGUE_BIAS),
|
1130 |
+
|
1131 |
+
/* ReLu gradient. Apply ReLu gradient to matmul output. Store ReLu gradient in the output matrix.
|
1132 |
+
*
|
1133 |
+
* This epilogue mode requires an extra input,
|
1134 |
+
* see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1135 |
+
*/
|
1136 |
+
CUBLASLT_EPILOGUE_DRELU = 8 | 128,
|
1137 |
+
|
1138 |
+
/* ReLu and Bias gradients. Apply independently ReLu and Bias gradient to
|
1139 |
+
* matmul output. Store ReLu gradient in the output matrix, and Bias gradient
|
1140 |
+
* in the auxiliary output (see CUBLASLT_MATMUL_DESC_BIAS_POINTER).
|
1141 |
+
*
|
1142 |
+
* This epilogue mode requires an extra input,
|
1143 |
+
* see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1144 |
+
*/
|
1145 |
+
CUBLASLT_EPILOGUE_DRELU_BGRAD = CUBLASLT_EPILOGUE_DRELU | 16,
|
1146 |
+
|
1147 |
+
/** GELU, apply GELU point-wise transform to the results (x:=GELU(x)).
|
1148 |
+
*/
|
1149 |
+
CUBLASLT_EPILOGUE_GELU = 32,
|
1150 |
+
|
1151 |
+
/** GELU, apply GELU point-wise transform to the results (x:=GELU(x)).
|
1152 |
+
*
|
1153 |
+
* This epilogue mode outputs GELU input as a separate matrix (useful for training).
|
1154 |
+
* See CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1155 |
+
*/
|
1156 |
+
CUBLASLT_EPILOGUE_GELU_AUX = (CUBLASLT_EPILOGUE_GELU | 128),
|
1157 |
+
|
1158 |
+
/** GELU and Bias, apply Bias and then GELU transform
|
1159 |
+
*/
|
1160 |
+
CUBLASLT_EPILOGUE_GELU_BIAS = (CUBLASLT_EPILOGUE_GELU | CUBLASLT_EPILOGUE_BIAS),
|
1161 |
+
|
1162 |
+
/** GELU and Bias, apply Bias and then GELU transform
|
1163 |
+
*
|
1164 |
+
* This epilogue mode outputs GELU input as a separate matrix (useful for training).
|
1165 |
+
* See CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1166 |
+
*/
|
1167 |
+
CUBLASLT_EPILOGUE_GELU_AUX_BIAS = (CUBLASLT_EPILOGUE_GELU_AUX | CUBLASLT_EPILOGUE_BIAS),
|
1168 |
+
|
1169 |
+
/* GELU gradient. Apply GELU gradient to matmul output. Store GELU gradient in the output matrix.
|
1170 |
+
*
|
1171 |
+
* This epilogue mode requires an extra input,
|
1172 |
+
* see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1173 |
+
*/
|
1174 |
+
CUBLASLT_EPILOGUE_DGELU = 64 | 128,
|
1175 |
+
|
1176 |
+
/* GELU and Bias gradients. Apply independently GELU and Bias gradient to
|
1177 |
+
* matmul output. Store GELU gradient in the output matrix, and Bias gradient
|
1178 |
+
* in the auxiliary output (see CUBLASLT_MATMUL_DESC_BIAS_POINTER).
|
1179 |
+
*
|
1180 |
+
* This epilogue mode requires an extra input,
|
1181 |
+
* see CUBLASLT_MATMUL_DESC_EPILOGUE_AUX_POINTER.
|
1182 |
+
*/
|
1183 |
+
CUBLASLT_EPILOGUE_DGELU_BGRAD = CUBLASLT_EPILOGUE_DGELU | 16,
|
1184 |
+
|
1185 |
+
/** Bias gradient based on the input matrix A.
|
1186 |
+
*
|
1187 |
+
* The bias size corresponds to the number of rows of the matrix D.
|
1188 |
+
* The reduction happens over the GEMM's "k" dimension.
|
1189 |
+
*
|
1190 |
+
* Stores Bias gradient in the auxiliary output
|
1191 |
+
* (see CUBLASLT_MATMUL_DESC_BIAS_POINTER).
|
1192 |
+
*/
|
1193 |
+
CUBLASLT_EPILOGUE_BGRADA = 256,
|
1194 |
+
|
1195 |
+
/** Bias gradient based on the input matrix B.
|
1196 |
+
*
|
1197 |
+
* The bias size corresponds to the number of columns of the matrix D.
|
1198 |
+
* The reduction happens over the GEMM's "k" dimension.
|
1199 |
+
*
|
1200 |
+
* Stores Bias gradient in the auxiliary output
|
1201 |
+
* (see CUBLASLT_MATMUL_DESC_BIAS_POINTER).
|
1202 |
+
*/
|
1203 |
+
CUBLASLT_EPILOGUE_BGRADB = 512,
|
1204 |
+
} cublasLtEpilogue_t;
|
1205 |
+
|
1206 |
+
/** Matmul heuristic search mode
|
1207 |
+
*/
|
1208 |
+
typedef enum {
|
1209 |
+
/** ask heuristics for best algo for given usecase
|
1210 |
+
*/
|
1211 |
+
CUBLASLT_SEARCH_BEST_FIT = 0,
|
1212 |
+
/** only try to find best config for preconfigured algo id
|
1213 |
+
*/
|
1214 |
+
CUBLASLT_SEARCH_LIMITED_BY_ALGO_ID = 1,
|
1215 |
+
/** reserved for future use
|
1216 |
+
*/
|
1217 |
+
CUBLASLT_SEARCH_RESERVED_02 = 2,
|
1218 |
+
/** reserved for future use
|
1219 |
+
*/
|
1220 |
+
CUBLASLT_SEARCH_RESERVED_03 = 3,
|
1221 |
+
/** reserved for future use
|
1222 |
+
*/
|
1223 |
+
CUBLASLT_SEARCH_RESERVED_04 = 4,
|
1224 |
+
/** reserved for future use
|
1225 |
+
*/
|
1226 |
+
CUBLASLT_SEARCH_RESERVED_05 = 5,
|
1227 |
+
} cublasLtMatmulSearch_t;
|
1228 |
+
|
1229 |
+
/** Algo search preference to fine tune the heuristic function. */
|
1230 |
+
typedef enum {
|
1231 |
+
/** Search mode, see cublasLtMatmulSearch_t.
|
1232 |
+
*
|
1233 |
+
* uint32_t, default: CUBLASLT_SEARCH_BEST_FIT
|
1234 |
+
*/
|
1235 |
+
CUBLASLT_MATMUL_PREF_SEARCH_MODE = 0,
|
1236 |
+
|
1237 |
+
/** Maximum allowed workspace size in bytes.
|
1238 |
+
*
|
1239 |
+
* uint64_t, default: 0 - no workspace allowed
|
1240 |
+
*/
|
1241 |
+
CUBLASLT_MATMUL_PREF_MAX_WORKSPACE_BYTES = 1,
|
1242 |
+
|
1243 |
+
/** Reduction scheme mask, see cublasLtReductionScheme_t. Filters heuristic result to only include algo configs that
|
1244 |
+
* use one of the required modes.
|
1245 |
+
*
|
1246 |
+
* E.g. mask value of 0x03 will allow only INPLACE and COMPUTE_TYPE reduction schemes.
|
1247 |
+
*
|
1248 |
+
* uint32_t, default: CUBLASLT_REDUCTION_SCHEME_MASK (allows all reduction schemes)
|
1249 |
+
*/
|
1250 |
+
CUBLASLT_MATMUL_PREF_REDUCTION_SCHEME_MASK = 3,
|
1251 |
+
|
1252 |
+
/** Minimum buffer alignment for matrix A (in bytes).
|
1253 |
+
*
|
1254 |
+
* Selecting a smaller value will exclude algorithms that can not work with matrix A that is not as strictly aligned
|
1255 |
+
* as they need.
|
1256 |
+
*
|
1257 |
+
* uint32_t, default: 256
|
1258 |
+
*/
|
1259 |
+
CUBLASLT_MATMUL_PREF_MIN_ALIGNMENT_A_BYTES = 5,
|
1260 |
+
|
1261 |
+
/** Minimum buffer alignment for matrix B (in bytes).
|
1262 |
+
*
|
1263 |
+
* Selecting a smaller value will exclude algorithms that can not work with matrix B that is not as strictly aligned
|
1264 |
+
* as they need.
|
1265 |
+
*
|
1266 |
+
* uint32_t, default: 256
|
1267 |
+
*/
|
1268 |
+
CUBLASLT_MATMUL_PREF_MIN_ALIGNMENT_B_BYTES = 6,
|
1269 |
+
|
1270 |
+
/** Minimum buffer alignment for matrix C (in bytes).
|
1271 |
+
*
|
1272 |
+
* Selecting a smaller value will exclude algorithms that can not work with matrix C that is not as strictly aligned
|
1273 |
+
* as they need.
|
1274 |
+
*
|
1275 |
+
* uint32_t, default: 256
|
1276 |
+
*/
|
1277 |
+
CUBLASLT_MATMUL_PREF_MIN_ALIGNMENT_C_BYTES = 7,
|
1278 |
+
|
1279 |
+
/** Minimum buffer alignment for matrix D (in bytes).
|
1280 |
+
*
|
1281 |
+
* Selecting a smaller value will exclude algorithms that can not work with matrix D that is not as strictly aligned
|
1282 |
+
* as they need.
|
1283 |
+
*
|
1284 |
+
* uint32_t, default: 256
|
1285 |
+
*/
|
1286 |
+
CUBLASLT_MATMUL_PREF_MIN_ALIGNMENT_D_BYTES = 8,
|
1287 |
+
|
1288 |
+
/** Maximum wave count.
|
1289 |
+
*
|
1290 |
+
* See cublasLtMatmulHeuristicResult_t::wavesCount.
|
1291 |
+
*
|
1292 |
+
* Selecting a non-zero value will exclude algorithms that report device utilization higher than specified.
|
1293 |
+
*
|
1294 |
+
* float, default: 0.0f
|
1295 |
+
*/
|
1296 |
+
CUBLASLT_MATMUL_PREF_MAX_WAVES_COUNT = 9,
|
1297 |
+
|
1298 |
+
/** Numerical implementation details mask, see cublasLtNumericalImplFlags_t. Filters heuristic result to only include
|
1299 |
+
* algorithms that use the allowed implementations.
|
1300 |
+
*
|
1301 |
+
* uint64_t, default: uint64_t(-1) (allow everything)
|
1302 |
+
*/
|
1303 |
+
CUBLASLT_MATMUL_PREF_IMPL_MASK = 12,
|
1304 |
+
} cublasLtMatmulPreferenceAttributes_t;
|
1305 |
+
|
1306 |
+
/** Internal. Do not use directly.
|
1307 |
+
*/
|
1308 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulPreferenceInit_internal(cublasLtMatmulPreference_t pref, size_t size);
|
1309 |
+
|
1310 |
+
/** Initialize matmul heuristic search preference descriptor in pre-allocated space.
|
1311 |
+
*
|
1312 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if size of the pre-allocated space is insufficient
|
1313 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
1314 |
+
*/
|
1315 |
+
static inline cublasStatus_t cublasLtMatmulPreferenceInit(cublasLtMatmulPreference_t pref) {
|
1316 |
+
return cublasLtMatmulPreferenceInit_internal(pref, sizeof(*pref));
|
1317 |
+
}
|
1318 |
+
|
1319 |
+
/** Create new matmul heuristic search preference descriptor.
|
1320 |
+
*
|
1321 |
+
* \retval CUBLAS_STATUS_ALLOC_FAILED if memory could not be allocated
|
1322 |
+
* \retval CUBLAS_STATUS_SUCCESS if desciptor was created successfully
|
1323 |
+
*/
|
1324 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulPreferenceCreate(cublasLtMatmulPreference_t* pref);
|
1325 |
+
|
1326 |
+
/** Destroy matmul heuristic search preference descriptor.
|
1327 |
+
*
|
1328 |
+
* \retval CUBLAS_STATUS_SUCCESS if operation was successful
|
1329 |
+
*/
|
1330 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulPreferenceDestroy(cublasLtMatmulPreference_t pref);
|
1331 |
+
|
1332 |
+
/** Set matmul heuristic search preference descriptor attribute.
|
1333 |
+
*
|
1334 |
+
* \param[in] pref The descriptor
|
1335 |
+
* \param[in] attr The attribute
|
1336 |
+
* \param[in] buf memory address containing the new value
|
1337 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1338 |
+
*
|
1339 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1340 |
+
* selected attribute
|
1341 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute was set successfully
|
1342 |
+
*/
|
1343 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulPreferenceSetAttribute( //
|
1344 |
+
cublasLtMatmulPreference_t pref,
|
1345 |
+
cublasLtMatmulPreferenceAttributes_t attr,
|
1346 |
+
const void* buf,
|
1347 |
+
size_t sizeInBytes);
|
1348 |
+
|
1349 |
+
/** Get matmul heuristic search preference descriptor attribute.
|
1350 |
+
*
|
1351 |
+
* \param[in] pref The descriptor
|
1352 |
+
* \param[in] attr The attribute
|
1353 |
+
* \param[out] buf memory address containing the new value
|
1354 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1355 |
+
* \param[out] sizeWritten only valid when return value is CUBLAS_STATUS_SUCCESS. If sizeInBytes is non-zero: number of
|
1356 |
+
* bytes actually written, if sizeInBytes is 0: number of bytes needed to write full contents
|
1357 |
+
*
|
1358 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if sizeInBytes is 0 and sizeWritten is NULL, or if sizeInBytes is non-zero
|
1359 |
+
* and buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1360 |
+
* selected attribute
|
1361 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute's value was successfully written to user memory
|
1362 |
+
*/
|
1363 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulPreferenceGetAttribute( //
|
1364 |
+
cublasLtMatmulPreference_t pref,
|
1365 |
+
cublasLtMatmulPreferenceAttributes_t attr,
|
1366 |
+
void* buf,
|
1367 |
+
size_t sizeInBytes,
|
1368 |
+
size_t* sizeWritten);
|
1369 |
+
|
1370 |
+
/** Results structure used by cublasLtMatmulGetAlgo.
|
1371 |
+
*
|
1372 |
+
* Holds returned configured algo descriptor and its runtime properties.
|
1373 |
+
*/
|
1374 |
+
typedef struct {
|
1375 |
+
/** Matmul algorithm descriptor.
|
1376 |
+
*
|
1377 |
+
* Must be initialized with cublasLtMatmulAlgoInit() if preferences' CUBLASLT_MATMUL_PERF_SEARCH_MODE is set to
|
1378 |
+
* CUBLASLT_SEARCH_LIMITED_BY_ALGO_ID
|
1379 |
+
*/
|
1380 |
+
cublasLtMatmulAlgo_t algo;
|
1381 |
+
|
1382 |
+
/** Actual size of workspace memory required.
|
1383 |
+
*/
|
1384 |
+
size_t workspaceSize;
|
1385 |
+
|
1386 |
+
/** Result status, other fields are only valid if after call to cublasLtMatmulAlgoGetHeuristic() this member is set to
|
1387 |
+
* CUBLAS_STATUS_SUCCESS.
|
1388 |
+
*/
|
1389 |
+
cublasStatus_t state;
|
1390 |
+
|
1391 |
+
/** Waves count - a device utilization metric.
|
1392 |
+
*
|
1393 |
+
* wavesCount value of 1.0f suggests that when kernel is launched it will fully occupy the GPU.
|
1394 |
+
*/
|
1395 |
+
float wavesCount;
|
1396 |
+
|
1397 |
+
int reserved[4];
|
1398 |
+
} cublasLtMatmulHeuristicResult_t;
|
1399 |
+
|
1400 |
+
/** Query cublasLt heuristic for algorithm appropriate for given use case.
|
1401 |
+
*
|
1402 |
+
* \param[in] lightHandle Pointer to the allocated cuBLASLt handle for the cuBLASLt
|
1403 |
+
* context. See cublasLtHandle_t.
|
1404 |
+
* \param[in] operationDesc Handle to the matrix multiplication descriptor.
|
1405 |
+
* \param[in] Adesc Handle to the layout descriptors for matrix A.
|
1406 |
+
* \param[in] Bdesc Handle to the layout descriptors for matrix B.
|
1407 |
+
* \param[in] Cdesc Handle to the layout descriptors for matrix C.
|
1408 |
+
* \param[in] Ddesc Handle to the layout descriptors for matrix D.
|
1409 |
+
* \param[in] preference Pointer to the structure holding the heuristic search
|
1410 |
+
* preferences descriptor. See cublasLtMatrixLayout_t.
|
1411 |
+
* \param[in] requestedAlgoCount Size of heuristicResultsArray (in elements) and requested
|
1412 |
+
* maximum number of algorithms to return.
|
1413 |
+
* \param[in, out] heuristicResultsArray Output algorithms and associated runtime characteristics,
|
1414 |
+
* ordered in increasing estimated compute time.
|
1415 |
+
* \param[out] returnAlgoCount The number of heuristicResultsArray elements written.
|
1416 |
+
*
|
1417 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if requestedAlgoCount is less or equal to zero
|
1418 |
+
* \retval CUBLAS_STATUS_NOT_SUPPORTED if no heuristic function available for current configuration
|
1419 |
+
* \retval CUBLAS_STATUS_SUCCESS if query was successful, inspect
|
1420 |
+
* heuristicResultsArray[0 to (returnAlgoCount - 1)].state
|
1421 |
+
* for detail status of results
|
1422 |
+
*/
|
1423 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoGetHeuristic(cublasLtHandle_t lightHandle,
|
1424 |
+
cublasLtMatmulDesc_t operationDesc,
|
1425 |
+
cublasLtMatrixLayout_t Adesc,
|
1426 |
+
cublasLtMatrixLayout_t Bdesc,
|
1427 |
+
cublasLtMatrixLayout_t Cdesc,
|
1428 |
+
cublasLtMatrixLayout_t Ddesc,
|
1429 |
+
cublasLtMatmulPreference_t preference,
|
1430 |
+
int requestedAlgoCount,
|
1431 |
+
cublasLtMatmulHeuristicResult_t heuristicResultsArray[],
|
1432 |
+
int* returnAlgoCount);
|
1433 |
+
|
1434 |
+
/* ---------------------------------------------------------------------------------------*/
|
1435 |
+
/* Lower level API to be able to implement own Heuristic and Find routines */
|
1436 |
+
/* ---------------------------------------------------------------------------------------*/
|
1437 |
+
|
1438 |
+
/** Routine to get all algo IDs that can potentially run
|
1439 |
+
*
|
1440 |
+
* \param[in] int requestedAlgoCount requested number of algos (must be less or equal to size of algoIdsA
|
1441 |
+
* (in elements)) \param[out] algoIdsA array to write algoIds to \param[out] returnAlgoCount number of algoIds
|
1442 |
+
* actually written
|
1443 |
+
*
|
1444 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if requestedAlgoCount is less or equal to zero
|
1445 |
+
* \retval CUBLAS_STATUS_SUCCESS if query was successful, inspect returnAlgoCount to get actual number of IDs
|
1446 |
+
* available
|
1447 |
+
*/
|
1448 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoGetIds(cublasLtHandle_t lightHandle,
|
1449 |
+
cublasComputeType_t computeType,
|
1450 |
+
cudaDataType_t scaleType,
|
1451 |
+
cudaDataType_t Atype,
|
1452 |
+
cudaDataType_t Btype,
|
1453 |
+
cudaDataType_t Ctype,
|
1454 |
+
cudaDataType_t Dtype,
|
1455 |
+
int requestedAlgoCount,
|
1456 |
+
int algoIdsArray[],
|
1457 |
+
int* returnAlgoCount);
|
1458 |
+
|
1459 |
+
/** Initialize algo structure
|
1460 |
+
*
|
1461 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if algo is NULL or algoId is outside of recognized range
|
1462 |
+
* \retval CUBLAS_STATUS_NOT_SUPPORTED if algoId is not supported for given combination of data types
|
1463 |
+
* \retval CUBLAS_STATUS_SUCCESS if the structure was successfully initialized
|
1464 |
+
*/
|
1465 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoInit(cublasLtHandle_t lightHandle,
|
1466 |
+
cublasComputeType_t computeType,
|
1467 |
+
cudaDataType_t scaleType,
|
1468 |
+
cudaDataType_t Atype,
|
1469 |
+
cudaDataType_t Btype,
|
1470 |
+
cudaDataType_t Ctype,
|
1471 |
+
cudaDataType_t Dtype,
|
1472 |
+
int algoId,
|
1473 |
+
cublasLtMatmulAlgo_t* algo);
|
1474 |
+
|
1475 |
+
/** Check configured algo descriptor for correctness and support on current device.
|
1476 |
+
*
|
1477 |
+
* Result includes required workspace size and calculated wave count.
|
1478 |
+
*
|
1479 |
+
* CUBLAS_STATUS_SUCCESS doesn't fully guarantee algo will run (will fail if e.g. buffers are not correctly aligned);
|
1480 |
+
* but if cublasLtMatmulAlgoCheck fails, the algo will not run.
|
1481 |
+
*
|
1482 |
+
* \param[in] algo algo configuration to check
|
1483 |
+
* \param[out] result result structure to report algo runtime characteristics; algo field is never updated
|
1484 |
+
*
|
1485 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if matrix layout descriptors or operation descriptor don't match algo
|
1486 |
+
* descriptor
|
1487 |
+
* \retval CUBLAS_STATUS_NOT_SUPPORTED if algo configuration or data type combination is not currently supported on
|
1488 |
+
* given device
|
1489 |
+
* \retval CUBLAS_STATUS_ARCH_MISMATCH if algo configuration cannot be run using the selected device
|
1490 |
+
* \retval CUBLAS_STATUS_SUCCESS if check was successful
|
1491 |
+
*/
|
1492 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoCheck( //
|
1493 |
+
cublasLtHandle_t lightHandle,
|
1494 |
+
cublasLtMatmulDesc_t operationDesc,
|
1495 |
+
cublasLtMatrixLayout_t Adesc,
|
1496 |
+
cublasLtMatrixLayout_t Bdesc,
|
1497 |
+
cublasLtMatrixLayout_t Cdesc,
|
1498 |
+
cublasLtMatrixLayout_t Ddesc,
|
1499 |
+
const cublasLtMatmulAlgo_t* algo, ///< may point to result->algo
|
1500 |
+
cublasLtMatmulHeuristicResult_t* result);
|
1501 |
+
|
1502 |
+
/** Capabilities Attributes that can be retrieved from an initialized Algo structure
|
1503 |
+
*/
|
1504 |
+
typedef enum {
|
1505 |
+
/** support for split K, see CUBLASLT_ALGO_CONFIG_SPLITK_NUM
|
1506 |
+
*
|
1507 |
+
* int32_t, 0 means no support, supported otherwise
|
1508 |
+
*/
|
1509 |
+
CUBLASLT_ALGO_CAP_SPLITK_SUPPORT = 0,
|
1510 |
+
|
1511 |
+
/** reduction scheme mask, see cublasLtReductionScheme_t; shows supported reduction schemes, if reduction scheme is
|
1512 |
+
* not masked out it is supported.
|
1513 |
+
*
|
1514 |
+
* e.g. int isReductionSchemeComputeTypeSupported ? (reductionSchemeMask & CUBLASLT_REDUCTION_SCHEME_COMPUTE_TYPE) ==
|
1515 |
+
* CUBLASLT_REDUCTION_SCHEME_COMPUTE_TYPE ? 1 : 0;
|
1516 |
+
*
|
1517 |
+
* uint32_t
|
1518 |
+
*/
|
1519 |
+
CUBLASLT_ALGO_CAP_REDUCTION_SCHEME_MASK = 1,
|
1520 |
+
|
1521 |
+
/** support for cta swizzling, see CUBLASLT_ALGO_CONFIG_CTA_SWIZZLING
|
1522 |
+
*
|
1523 |
+
* uint32_t, 0 means no support, 1 means supported value of 1, other values are reserved
|
1524 |
+
*/
|
1525 |
+
CUBLASLT_ALGO_CAP_CTA_SWIZZLING_SUPPORT = 2,
|
1526 |
+
|
1527 |
+
/** support strided batch
|
1528 |
+
*
|
1529 |
+
* int32_t, 0 means no support, supported otherwise
|
1530 |
+
*/
|
1531 |
+
CUBLASLT_ALGO_CAP_STRIDED_BATCH_SUPPORT = 3,
|
1532 |
+
|
1533 |
+
/** support results out of place (D != C in D = alpha.A.B + beta.C)
|
1534 |
+
*
|
1535 |
+
* int32_t, 0 means no support, supported otherwise
|
1536 |
+
*/
|
1537 |
+
CUBLASLT_ALGO_CAP_OUT_OF_PLACE_RESULT_SUPPORT = 4,
|
1538 |
+
|
1539 |
+
/** syrk/herk support (on top of regular gemm)
|
1540 |
+
*
|
1541 |
+
* int32_t, 0 means no support, supported otherwise
|
1542 |
+
*/
|
1543 |
+
CUBLASLT_ALGO_CAP_UPLO_SUPPORT = 5,
|
1544 |
+
|
1545 |
+
/** tile ids possible to use, see cublasLtMatmulTile_t; if no tile ids are supported use
|
1546 |
+
* CUBLASLT_MATMUL_TILE_UNDEFINED
|
1547 |
+
*
|
1548 |
+
* use cublasLtMatmulAlgoCapGetAttribute() with sizeInBytes=0 to query actual count
|
1549 |
+
*
|
1550 |
+
* array of uint32_t
|
1551 |
+
*/
|
1552 |
+
CUBLASLT_ALGO_CAP_TILE_IDS = 6,
|
1553 |
+
|
1554 |
+
/** custom option range is from 0 to CUBLASLT_ALGO_CAP_CUSTOM_OPTION_MAX (inclusive), see
|
1555 |
+
* CUBLASLT_ALGO_CONFIG_CUSTOM_OPTION
|
1556 |
+
*
|
1557 |
+
* int32_t
|
1558 |
+
*/
|
1559 |
+
CUBLASLT_ALGO_CAP_CUSTOM_OPTION_MAX = 7,
|
1560 |
+
|
1561 |
+
/** whether algorithm supports custom (not COL or ROW memory order), see cublasLtOrder_t
|
1562 |
+
*
|
1563 |
+
* int32_t 0 means only COL and ROW memory order is allowed, non-zero means that algo might have different
|
1564 |
+
* requirements;
|
1565 |
+
*/
|
1566 |
+
CUBLASLT_ALGO_CAP_CUSTOM_MEMORY_ORDER = 10,
|
1567 |
+
|
1568 |
+
/** bitmask enumerating pointer modes algorithm supports
|
1569 |
+
*
|
1570 |
+
* uint32_t, see cublasLtPointerModeMask_t
|
1571 |
+
*/
|
1572 |
+
CUBLASLT_ALGO_CAP_POINTER_MODE_MASK = 11,
|
1573 |
+
|
1574 |
+
/** bitmask enumerating kinds of postprocessing algorithm supports in the epilogue
|
1575 |
+
*
|
1576 |
+
* uint32_t, see cublasLtEpilogue_t
|
1577 |
+
*/
|
1578 |
+
CUBLASLT_ALGO_CAP_EPILOGUE_MASK = 12,
|
1579 |
+
|
1580 |
+
/** stages ids possible to use, see cublasLtMatmulStages_t; if no stages ids are supported use
|
1581 |
+
* CUBLASLT_MATMUL_STAGES_UNDEFINED
|
1582 |
+
*
|
1583 |
+
* use cublasLtMatmulAlgoCapGetAttribute() with sizeInBytes=0 to query actual count
|
1584 |
+
*
|
1585 |
+
* array of uint32_t
|
1586 |
+
*/
|
1587 |
+
CUBLASLT_ALGO_CAP_STAGES_IDS = 13,
|
1588 |
+
|
1589 |
+
/** support for nagative ld for all of the matrices
|
1590 |
+
*
|
1591 |
+
* int32_t 0 means no support, supported otherwise
|
1592 |
+
*/
|
1593 |
+
CUBLASLT_ALGO_CAP_LD_NEGATIVE = 14,
|
1594 |
+
|
1595 |
+
/** details about algorithm's implementation that affect it's numerical behavior
|
1596 |
+
*
|
1597 |
+
* uint64_t, see cublasLtNumericalImplFlags_t
|
1598 |
+
*/
|
1599 |
+
CUBLASLT_ALGO_CAP_NUMERICAL_IMPL_FLAGS = 15,
|
1600 |
+
|
1601 |
+
/** minimum alignment required for A matrix in bytes
|
1602 |
+
* (required for buffer pointer, leading dimension, and possibly other strides defined for matrix memory order)
|
1603 |
+
*
|
1604 |
+
* uint32_t
|
1605 |
+
*/
|
1606 |
+
CUBLASLT_ALGO_CAP_MIN_ALIGNMENT_A_BYTES = 16,
|
1607 |
+
|
1608 |
+
/** minimum alignment required for B matrix in bytes
|
1609 |
+
* (required for buffer pointer, leading dimension, and possibly other strides defined for matrix memory order)
|
1610 |
+
*
|
1611 |
+
* uint32_t
|
1612 |
+
*/
|
1613 |
+
CUBLASLT_ALGO_CAP_MIN_ALIGNMENT_B_BYTES = 17,
|
1614 |
+
|
1615 |
+
/** minimum alignment required for C matrix in bytes
|
1616 |
+
* (required for buffer pointer, leading dimension, and possibly other strides defined for matrix memory order)
|
1617 |
+
*
|
1618 |
+
* uint32_t
|
1619 |
+
*/
|
1620 |
+
CUBLASLT_ALGO_CAP_MIN_ALIGNMENT_C_BYTES = 18,
|
1621 |
+
|
1622 |
+
/** minimum alignment required for D matrix in bytes
|
1623 |
+
* (required for buffer pointer, leading dimension, and possibly other strides defined for matrix memory order)
|
1624 |
+
*
|
1625 |
+
* uint32_t
|
1626 |
+
*/
|
1627 |
+
CUBLASLT_ALGO_CAP_MIN_ALIGNMENT_D_BYTES = 19,
|
1628 |
+
} cublasLtMatmulAlgoCapAttributes_t;
|
1629 |
+
|
1630 |
+
/** Get algo capability attribute.
|
1631 |
+
*
|
1632 |
+
* E.g. to get list of supported Tile IDs:
|
1633 |
+
* cublasLtMatmulTile_t tiles[CUBLASLT_MATMUL_TILE_END];
|
1634 |
+
* size_t num_tiles, size_written;
|
1635 |
+
* if (cublasLtMatmulAlgoCapGetAttribute(algo, CUBLASLT_ALGO_CAP_TILE_IDS, tiles, sizeof(tiles), size_written) ==
|
1636 |
+
* CUBLAS_STATUS_SUCCESS) { num_tiles = size_written / sizeof(tiles[0]);
|
1637 |
+
* }
|
1638 |
+
*
|
1639 |
+
* \param[in] algo The algo descriptor
|
1640 |
+
* \param[in] attr The attribute
|
1641 |
+
* \param[out] buf memory address containing the new value
|
1642 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1643 |
+
* \param[out] sizeWritten only valid when return value is CUBLAS_STATUS_SUCCESS. If sizeInBytes is non-zero: number of
|
1644 |
+
* bytes actually written, if sizeInBytes is 0: number of bytes needed to write full contents
|
1645 |
+
*
|
1646 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if sizeInBytes is 0 and sizeWritten is NULL, or if sizeInBytes is non-zero
|
1647 |
+
* and buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1648 |
+
* selected attribute
|
1649 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute's value was successfully written to user memory
|
1650 |
+
*/
|
1651 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoCapGetAttribute(const cublasLtMatmulAlgo_t* algo,
|
1652 |
+
cublasLtMatmulAlgoCapAttributes_t attr,
|
1653 |
+
void* buf,
|
1654 |
+
size_t sizeInBytes,
|
1655 |
+
size_t* sizeWritten);
|
1656 |
+
|
1657 |
+
/** Algo Configuration Attributes that can be set according to the Algo capabilities
|
1658 |
+
*/
|
1659 |
+
typedef enum {
|
1660 |
+
/** algorithm index, see cublasLtMatmulAlgoGetIds()
|
1661 |
+
*
|
1662 |
+
* readonly, set by cublasLtMatmulAlgoInit()
|
1663 |
+
* int32_t
|
1664 |
+
*/
|
1665 |
+
CUBLASLT_ALGO_CONFIG_ID = 0,
|
1666 |
+
/** tile id, see cublasLtMatmulTile_t
|
1667 |
+
*
|
1668 |
+
* uint32_t, default: CUBLASLT_MATMUL_TILE_UNDEFINED
|
1669 |
+
*/
|
1670 |
+
CUBLASLT_ALGO_CONFIG_TILE_ID = 1,
|
1671 |
+
/** Number of K splits. If the number of K splits is greater than one, SPLITK_NUM parts
|
1672 |
+
* of matrix multiplication will be computed in parallel. The results will be accumulated
|
1673 |
+
* according to CUBLASLT_ALGO_CONFIG_REDUCTION_SCHEME
|
1674 |
+
*
|
1675 |
+
* int32_t, default: 1
|
1676 |
+
*/
|
1677 |
+
CUBLASLT_ALGO_CONFIG_SPLITK_NUM = 2,
|
1678 |
+
/** reduction scheme, see cublasLtReductionScheme_t
|
1679 |
+
*
|
1680 |
+
* uint32_t, default: CUBLASLT_REDUCTION_SCHEME_NONE
|
1681 |
+
*/
|
1682 |
+
CUBLASLT_ALGO_CONFIG_REDUCTION_SCHEME = 3,
|
1683 |
+
/** cta swizzling, change mapping from CUDA grid coordinates to parts of the matrices
|
1684 |
+
*
|
1685 |
+
* possible values: 0, 1, other values reserved
|
1686 |
+
*
|
1687 |
+
* uint32_t, default: 0
|
1688 |
+
*/
|
1689 |
+
CUBLASLT_ALGO_CONFIG_CTA_SWIZZLING = 4,
|
1690 |
+
/** custom option, each algorithm can support some custom options that don't fit description of the other config
|
1691 |
+
* attributes, see CUBLASLT_ALGO_CAP_CUSTOM_OPTION_MAX to get accepted range for any specific case
|
1692 |
+
*
|
1693 |
+
* uint32_t, default: 0
|
1694 |
+
*/
|
1695 |
+
CUBLASLT_ALGO_CONFIG_CUSTOM_OPTION = 5,
|
1696 |
+
/** stages id, see cublasLtMatmulStages_t
|
1697 |
+
*
|
1698 |
+
* uint32_t, default: CUBLASLT_MATMUL_STAGES_UNDEFINED
|
1699 |
+
*/
|
1700 |
+
CUBLASLT_ALGO_CONFIG_STAGES_ID = 6,
|
1701 |
+
/** inner shape id, see cublasLtMatmulInnerShape_t
|
1702 |
+
*
|
1703 |
+
* uint16_t, default: 0 (CUBLASLT_MATMUL_INNER_SHAPE_UNDEFINED)
|
1704 |
+
*/
|
1705 |
+
CUBLASLT_ALGO_CONFIG_INNER_SHAPE_ID = 7,
|
1706 |
+
/** Thread Block Cluster shape id, see cublasLtClusterShape_t. Defines cluster size to use.
|
1707 |
+
*
|
1708 |
+
* uint16_t, default: 0 (CUBLASLT_CLUSTER_SHAPE_AUTO)
|
1709 |
+
*/
|
1710 |
+
CUBLASLT_ALGO_CONFIG_CLUSTER_SHAPE_ID = 8,
|
1711 |
+
} cublasLtMatmulAlgoConfigAttributes_t;
|
1712 |
+
|
1713 |
+
/** Set algo configuration attribute.
|
1714 |
+
*
|
1715 |
+
* \param[in] algo The algo descriptor
|
1716 |
+
* \param[in] attr The attribute
|
1717 |
+
* \param[in] buf memory address containing the new value
|
1718 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1719 |
+
*
|
1720 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1721 |
+
* selected attribute
|
1722 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute was set successfully
|
1723 |
+
*/
|
1724 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoConfigSetAttribute(cublasLtMatmulAlgo_t* algo,
|
1725 |
+
cublasLtMatmulAlgoConfigAttributes_t attr,
|
1726 |
+
const void* buf,
|
1727 |
+
size_t sizeInBytes);
|
1728 |
+
|
1729 |
+
/** Get algo configuration attribute.
|
1730 |
+
*
|
1731 |
+
* \param[in] algo The algo descriptor
|
1732 |
+
* \param[in] attr The attribute
|
1733 |
+
* \param[out] buf memory address containing the new value
|
1734 |
+
* \param[in] sizeInBytes size of buf buffer for verification (in bytes)
|
1735 |
+
* \param[out] sizeWritten only valid when return value is CUBLAS_STATUS_SUCCESS. If sizeInBytes is non-zero: number of
|
1736 |
+
* bytes actually written, if sizeInBytes is 0: number of bytes needed to write full contents
|
1737 |
+
*
|
1738 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if sizeInBytes is 0 and sizeWritten is NULL, or if sizeInBytes is non-zero
|
1739 |
+
* and buf is NULL or sizeInBytes doesn't match size of internal storage for
|
1740 |
+
* selected attribute
|
1741 |
+
* \retval CUBLAS_STATUS_SUCCESS if attribute's value was successfully written to user memory
|
1742 |
+
*/
|
1743 |
+
cublasStatus_t CUBLASWINAPI cublasLtMatmulAlgoConfigGetAttribute(const cublasLtMatmulAlgo_t* algo,
|
1744 |
+
cublasLtMatmulAlgoConfigAttributes_t attr,
|
1745 |
+
void* buf,
|
1746 |
+
size_t sizeInBytes,
|
1747 |
+
size_t* sizeWritten);
|
1748 |
+
|
1749 |
+
/** Experimental: Logger callback type.
|
1750 |
+
*/
|
1751 |
+
typedef void (*cublasLtLoggerCallback_t)(int logLevel, const char* functionName, const char* message);
|
1752 |
+
|
1753 |
+
/** Experimental: Logger callback setter.
|
1754 |
+
*
|
1755 |
+
* \param[in] callback a user defined callback function to be called by the logger
|
1756 |
+
*
|
1757 |
+
* \retval CUBLAS_STATUS_SUCCESS if callback was set successfully
|
1758 |
+
*/
|
1759 |
+
cublasStatus_t CUBLASWINAPI cublasLtLoggerSetCallback(cublasLtLoggerCallback_t callback);
|
1760 |
+
|
1761 |
+
/** Experimental: Log file setter.
|
1762 |
+
*
|
1763 |
+
* \param[in] file an open file with write permissions
|
1764 |
+
*
|
1765 |
+
* \retval CUBLAS_STATUS_SUCCESS if log file was set successfully
|
1766 |
+
*/
|
1767 |
+
cublasStatus_t CUBLASWINAPI cublasLtLoggerSetFile(FILE* file);
|
1768 |
+
|
1769 |
+
/** Experimental: Open log file.
|
1770 |
+
*
|
1771 |
+
* \param[in] logFile log file path. if the log file does not exist, it will be created
|
1772 |
+
*
|
1773 |
+
* \retval CUBLAS_STATUS_SUCCESS if log file was created successfully
|
1774 |
+
*/
|
1775 |
+
cublasStatus_t CUBLASWINAPI cublasLtLoggerOpenFile(const char* logFile);
|
1776 |
+
|
1777 |
+
/** Experimental: Log level setter.
|
1778 |
+
*
|
1779 |
+
* \param[in] level log level, should be one of the following:
|
1780 |
+
* 0. Off
|
1781 |
+
* 1. Errors
|
1782 |
+
* 2. Performance Trace
|
1783 |
+
* 3. Performance Hints
|
1784 |
+
* 4. Heuristics Trace
|
1785 |
+
* 5. API Trace
|
1786 |
+
*
|
1787 |
+
* \retval CUBLAS_STATUS_INVALID_VALUE if log level is not one of the above levels
|
1788 |
+
*
|
1789 |
+
* \retval CUBLAS_STATUS_SUCCESS if log level was set successfully
|
1790 |
+
*/
|
1791 |
+
cublasStatus_t CUBLASWINAPI cublasLtLoggerSetLevel(int level);
|
1792 |
+
|
1793 |
+
/** Experimental: Log mask setter.
|
1794 |
+
*
|
1795 |
+
* \param[in] mask log mask, should be a combination of the following masks:
|
1796 |
+
* 0. Off
|
1797 |
+
* 1. Errors
|
1798 |
+
* 2. Performance Trace
|
1799 |
+
* 4. Performance Hints
|
1800 |
+
* 8. Heuristics Trace
|
1801 |
+
* 16. API Trace
|
1802 |
+
*
|
1803 |
+
* \retval CUBLAS_STATUS_SUCCESS if log mask was set successfully
|
1804 |
+
*/
|
1805 |
+
cublasStatus_t CUBLASWINAPI cublasLtLoggerSetMask(int mask);
|
1806 |
+
|
1807 |
+
/** Experimental: Disable logging for the entire session.
|
1808 |
+
*
|
1809 |
+
* \retval CUBLAS_STATUS_SUCCESS if disabled logging
|
1810 |
+
*/
|
1811 |
+
cublasStatus_t CUBLASWINAPI cublasLtLoggerForceDisable();
|
1812 |
+
|
1813 |
+
#if defined(__cplusplus)
|
1814 |
+
}
|
1815 |
+
#endif /* __cplusplus */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublasXt.h
ADDED
@@ -0,0 +1,693 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
1 |
+
/*
|
2 |
+
* Copyright 1993-2019 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
/* cublasXt : Host API, Out of Core and Multi-GPU BLAS Library
|
51 |
+
|
52 |
+
*/
|
53 |
+
|
54 |
+
#if !defined(CUBLAS_XT_H_)
|
55 |
+
#define CUBLAS_XT_H_
|
56 |
+
|
57 |
+
#include "driver_types.h"
|
58 |
+
#include "cuComplex.h" /* import complex data type */
|
59 |
+
|
60 |
+
#include "cublas_v2.h"
|
61 |
+
|
62 |
+
#if defined(__cplusplus)
|
63 |
+
extern "C" {
|
64 |
+
#endif /* __cplusplus */
|
65 |
+
|
66 |
+
struct cublasXtContext;
|
67 |
+
typedef struct cublasXtContext* cublasXtHandle_t;
|
68 |
+
|
69 |
+
cublasStatus_t CUBLASWINAPI cublasXtCreate(cublasXtHandle_t* handle);
|
70 |
+
cublasStatus_t CUBLASWINAPI cublasXtDestroy(cublasXtHandle_t handle);
|
71 |
+
cublasStatus_t CUBLASWINAPI cublasXtGetNumBoards(int nbDevices, int deviceId[], int* nbBoards);
|
72 |
+
cublasStatus_t CUBLASWINAPI cublasXtMaxBoards(int* nbGpuBoards);
|
73 |
+
/* This routine selects the Gpus that the user want to use for CUBLAS-XT */
|
74 |
+
cublasStatus_t CUBLASWINAPI cublasXtDeviceSelect(cublasXtHandle_t handle, int nbDevices, int deviceId[]);
|
75 |
+
|
76 |
+
/* This routine allows to change the dimension of the tiles ( blockDim x blockDim ) */
|
77 |
+
cublasStatus_t CUBLASWINAPI cublasXtSetBlockDim(cublasXtHandle_t handle, int blockDim);
|
78 |
+
cublasStatus_t CUBLASWINAPI cublasXtGetBlockDim(cublasXtHandle_t handle, int* blockDim);
|
79 |
+
|
80 |
+
typedef enum { CUBLASXT_PINNING_DISABLED = 0, CUBLASXT_PINNING_ENABLED = 1 } cublasXtPinnedMemMode_t;
|
81 |
+
/* This routine allows to CUBLAS-XT to pin the Host memory if it find out that some of the matrix passed
|
82 |
+
are not pinned : Pinning/Unpinning the Host memory is still a costly operation
|
83 |
+
It is better if the user controls the memory on its own (by pinning/unpinning oly when necessary)
|
84 |
+
*/
|
85 |
+
cublasStatus_t CUBLASWINAPI cublasXtGetPinningMemMode(cublasXtHandle_t handle, cublasXtPinnedMemMode_t* mode);
|
86 |
+
cublasStatus_t CUBLASWINAPI cublasXtSetPinningMemMode(cublasXtHandle_t handle, cublasXtPinnedMemMode_t mode);
|
87 |
+
|
88 |
+
/* This routines is to provide a CPU Blas routines, used for too small sizes or hybrid computation */
|
89 |
+
typedef enum {
|
90 |
+
CUBLASXT_FLOAT = 0,
|
91 |
+
CUBLASXT_DOUBLE = 1,
|
92 |
+
CUBLASXT_COMPLEX = 2,
|
93 |
+
CUBLASXT_DOUBLECOMPLEX = 3,
|
94 |
+
} cublasXtOpType_t;
|
95 |
+
|
96 |
+
typedef enum {
|
97 |
+
CUBLASXT_GEMM = 0,
|
98 |
+
CUBLASXT_SYRK = 1,
|
99 |
+
CUBLASXT_HERK = 2,
|
100 |
+
CUBLASXT_SYMM = 3,
|
101 |
+
CUBLASXT_HEMM = 4,
|
102 |
+
CUBLASXT_TRSM = 5,
|
103 |
+
CUBLASXT_SYR2K = 6,
|
104 |
+
CUBLASXT_HER2K = 7,
|
105 |
+
|
106 |
+
CUBLASXT_SPMM = 8,
|
107 |
+
CUBLASXT_SYRKX = 9,
|
108 |
+
CUBLASXT_HERKX = 10,
|
109 |
+
CUBLASXT_TRMM = 11,
|
110 |
+
CUBLASXT_ROUTINE_MAX = 12,
|
111 |
+
} cublasXtBlasOp_t;
|
112 |
+
|
113 |
+
/* Currently only 32-bit integer BLAS routines are supported */
|
114 |
+
cublasStatus_t CUBLASWINAPI cublasXtSetCpuRoutine(cublasXtHandle_t handle,
|
115 |
+
cublasXtBlasOp_t blasOp,
|
116 |
+
cublasXtOpType_t type,
|
117 |
+
void* blasFunctor);
|
118 |
+
|
119 |
+
/* Specified the percentage of work that should done by the CPU, default is 0 (no work) */
|
120 |
+
cublasStatus_t CUBLASWINAPI cublasXtSetCpuRatio(cublasXtHandle_t handle,
|
121 |
+
cublasXtBlasOp_t blasOp,
|
122 |
+
cublasXtOpType_t type,
|
123 |
+
float ratio);
|
124 |
+
|
125 |
+
/* GEMM */
|
126 |
+
cublasStatus_t CUBLASWINAPI cublasXtSgemm(cublasXtHandle_t handle,
|
127 |
+
cublasOperation_t transa,
|
128 |
+
cublasOperation_t transb,
|
129 |
+
size_t m,
|
130 |
+
size_t n,
|
131 |
+
size_t k,
|
132 |
+
const float* alpha,
|
133 |
+
const float* A,
|
134 |
+
size_t lda,
|
135 |
+
const float* B,
|
136 |
+
size_t ldb,
|
137 |
+
const float* beta,
|
138 |
+
float* C,
|
139 |
+
size_t ldc);
|
140 |
+
|
141 |
+
cublasStatus_t CUBLASWINAPI cublasXtDgemm(cublasXtHandle_t handle,
|
142 |
+
cublasOperation_t transa,
|
143 |
+
cublasOperation_t transb,
|
144 |
+
size_t m,
|
145 |
+
size_t n,
|
146 |
+
size_t k,
|
147 |
+
const double* alpha,
|
148 |
+
const double* A,
|
149 |
+
size_t lda,
|
150 |
+
const double* B,
|
151 |
+
size_t ldb,
|
152 |
+
const double* beta,
|
153 |
+
double* C,
|
154 |
+
size_t ldc);
|
155 |
+
|
156 |
+
cublasStatus_t CUBLASWINAPI cublasXtCgemm(cublasXtHandle_t handle,
|
157 |
+
cublasOperation_t transa,
|
158 |
+
cublasOperation_t transb,
|
159 |
+
size_t m,
|
160 |
+
size_t n,
|
161 |
+
size_t k,
|
162 |
+
const cuComplex* alpha,
|
163 |
+
const cuComplex* A,
|
164 |
+
size_t lda,
|
165 |
+
const cuComplex* B,
|
166 |
+
size_t ldb,
|
167 |
+
const cuComplex* beta,
|
168 |
+
cuComplex* C,
|
169 |
+
size_t ldc);
|
170 |
+
|
171 |
+
cublasStatus_t CUBLASWINAPI cublasXtZgemm(cublasXtHandle_t handle,
|
172 |
+
cublasOperation_t transa,
|
173 |
+
cublasOperation_t transb,
|
174 |
+
size_t m,
|
175 |
+
size_t n,
|
176 |
+
size_t k,
|
177 |
+
const cuDoubleComplex* alpha,
|
178 |
+
const cuDoubleComplex* A,
|
179 |
+
size_t lda,
|
180 |
+
const cuDoubleComplex* B,
|
181 |
+
size_t ldb,
|
182 |
+
const cuDoubleComplex* beta,
|
183 |
+
cuDoubleComplex* C,
|
184 |
+
size_t ldc);
|
185 |
+
/* ------------------------------------------------------- */
|
186 |
+
/* SYRK */
|
187 |
+
cublasStatus_t CUBLASWINAPI cublasXtSsyrk(cublasXtHandle_t handle,
|
188 |
+
cublasFillMode_t uplo,
|
189 |
+
cublasOperation_t trans,
|
190 |
+
size_t n,
|
191 |
+
size_t k,
|
192 |
+
const float* alpha,
|
193 |
+
const float* A,
|
194 |
+
size_t lda,
|
195 |
+
const float* beta,
|
196 |
+
float* C,
|
197 |
+
size_t ldc);
|
198 |
+
|
199 |
+
cublasStatus_t CUBLASWINAPI cublasXtDsyrk(cublasXtHandle_t handle,
|
200 |
+
cublasFillMode_t uplo,
|
201 |
+
cublasOperation_t trans,
|
202 |
+
size_t n,
|
203 |
+
size_t k,
|
204 |
+
const double* alpha,
|
205 |
+
const double* A,
|
206 |
+
size_t lda,
|
207 |
+
const double* beta,
|
208 |
+
double* C,
|
209 |
+
size_t ldc);
|
210 |
+
|
211 |
+
cublasStatus_t CUBLASWINAPI cublasXtCsyrk(cublasXtHandle_t handle,
|
212 |
+
cublasFillMode_t uplo,
|
213 |
+
cublasOperation_t trans,
|
214 |
+
size_t n,
|
215 |
+
size_t k,
|
216 |
+
const cuComplex* alpha,
|
217 |
+
const cuComplex* A,
|
218 |
+
size_t lda,
|
219 |
+
const cuComplex* beta,
|
220 |
+
cuComplex* C,
|
221 |
+
size_t ldc);
|
222 |
+
|
223 |
+
cublasStatus_t CUBLASWINAPI cublasXtZsyrk(cublasXtHandle_t handle,
|
224 |
+
cublasFillMode_t uplo,
|
225 |
+
cublasOperation_t trans,
|
226 |
+
size_t n,
|
227 |
+
size_t k,
|
228 |
+
const cuDoubleComplex* alpha,
|
229 |
+
const cuDoubleComplex* A,
|
230 |
+
size_t lda,
|
231 |
+
const cuDoubleComplex* beta,
|
232 |
+
cuDoubleComplex* C,
|
233 |
+
size_t ldc);
|
234 |
+
/* -------------------------------------------------------------------- */
|
235 |
+
/* HERK */
|
236 |
+
cublasStatus_t CUBLASWINAPI cublasXtCherk(cublasXtHandle_t handle,
|
237 |
+
cublasFillMode_t uplo,
|
238 |
+
cublasOperation_t trans,
|
239 |
+
size_t n,
|
240 |
+
size_t k,
|
241 |
+
const float* alpha,
|
242 |
+
const cuComplex* A,
|
243 |
+
size_t lda,
|
244 |
+
const float* beta,
|
245 |
+
cuComplex* C,
|
246 |
+
size_t ldc);
|
247 |
+
|
248 |
+
cublasStatus_t CUBLASWINAPI cublasXtZherk(cublasXtHandle_t handle,
|
249 |
+
cublasFillMode_t uplo,
|
250 |
+
cublasOperation_t trans,
|
251 |
+
size_t n,
|
252 |
+
size_t k,
|
253 |
+
const double* alpha,
|
254 |
+
const cuDoubleComplex* A,
|
255 |
+
size_t lda,
|
256 |
+
const double* beta,
|
257 |
+
cuDoubleComplex* C,
|
258 |
+
size_t ldc);
|
259 |
+
/* -------------------------------------------------------------------- */
|
260 |
+
/* SYR2K */
|
261 |
+
cublasStatus_t CUBLASWINAPI cublasXtSsyr2k(cublasXtHandle_t handle,
|
262 |
+
cublasFillMode_t uplo,
|
263 |
+
cublasOperation_t trans,
|
264 |
+
size_t n,
|
265 |
+
size_t k,
|
266 |
+
const float* alpha,
|
267 |
+
const float* A,
|
268 |
+
size_t lda,
|
269 |
+
const float* B,
|
270 |
+
size_t ldb,
|
271 |
+
const float* beta,
|
272 |
+
float* C,
|
273 |
+
size_t ldc);
|
274 |
+
|
275 |
+
cublasStatus_t CUBLASWINAPI cublasXtDsyr2k(cublasXtHandle_t handle,
|
276 |
+
cublasFillMode_t uplo,
|
277 |
+
cublasOperation_t trans,
|
278 |
+
size_t n,
|
279 |
+
size_t k,
|
280 |
+
const double* alpha,
|
281 |
+
const double* A,
|
282 |
+
size_t lda,
|
283 |
+
const double* B,
|
284 |
+
size_t ldb,
|
285 |
+
const double* beta,
|
286 |
+
double* C,
|
287 |
+
size_t ldc);
|
288 |
+
|
289 |
+
cublasStatus_t CUBLASWINAPI cublasXtCsyr2k(cublasXtHandle_t handle,
|
290 |
+
cublasFillMode_t uplo,
|
291 |
+
cublasOperation_t trans,
|
292 |
+
size_t n,
|
293 |
+
size_t k,
|
294 |
+
const cuComplex* alpha,
|
295 |
+
const cuComplex* A,
|
296 |
+
size_t lda,
|
297 |
+
const cuComplex* B,
|
298 |
+
size_t ldb,
|
299 |
+
const cuComplex* beta,
|
300 |
+
cuComplex* C,
|
301 |
+
size_t ldc);
|
302 |
+
|
303 |
+
cublasStatus_t CUBLASWINAPI cublasXtZsyr2k(cublasXtHandle_t handle,
|
304 |
+
cublasFillMode_t uplo,
|
305 |
+
cublasOperation_t trans,
|
306 |
+
size_t n,
|
307 |
+
size_t k,
|
308 |
+
const cuDoubleComplex* alpha,
|
309 |
+
const cuDoubleComplex* A,
|
310 |
+
size_t lda,
|
311 |
+
const cuDoubleComplex* B,
|
312 |
+
size_t ldb,
|
313 |
+
const cuDoubleComplex* beta,
|
314 |
+
cuDoubleComplex* C,
|
315 |
+
size_t ldc);
|
316 |
+
/* -------------------------------------------------------------------- */
|
317 |
+
/* HERKX : variant extension of HERK */
|
318 |
+
cublasStatus_t CUBLASWINAPI cublasXtCherkx(cublasXtHandle_t handle,
|
319 |
+
cublasFillMode_t uplo,
|
320 |
+
cublasOperation_t trans,
|
321 |
+
size_t n,
|
322 |
+
size_t k,
|
323 |
+
const cuComplex* alpha,
|
324 |
+
const cuComplex* A,
|
325 |
+
size_t lda,
|
326 |
+
const cuComplex* B,
|
327 |
+
size_t ldb,
|
328 |
+
const float* beta,
|
329 |
+
cuComplex* C,
|
330 |
+
size_t ldc);
|
331 |
+
|
332 |
+
cublasStatus_t CUBLASWINAPI cublasXtZherkx(cublasXtHandle_t handle,
|
333 |
+
cublasFillMode_t uplo,
|
334 |
+
cublasOperation_t trans,
|
335 |
+
size_t n,
|
336 |
+
size_t k,
|
337 |
+
const cuDoubleComplex* alpha,
|
338 |
+
const cuDoubleComplex* A,
|
339 |
+
size_t lda,
|
340 |
+
const cuDoubleComplex* B,
|
341 |
+
size_t ldb,
|
342 |
+
const double* beta,
|
343 |
+
cuDoubleComplex* C,
|
344 |
+
size_t ldc);
|
345 |
+
|
346 |
+
/* -------------------------------------------------------------------- */
|
347 |
+
/* TRSM */
|
348 |
+
cublasStatus_t CUBLASWINAPI cublasXtStrsm(cublasXtHandle_t handle,
|
349 |
+
cublasSideMode_t side,
|
350 |
+
cublasFillMode_t uplo,
|
351 |
+
cublasOperation_t trans,
|
352 |
+
cublasDiagType_t diag,
|
353 |
+
size_t m,
|
354 |
+
size_t n,
|
355 |
+
const float* alpha,
|
356 |
+
const float* A,
|
357 |
+
size_t lda,
|
358 |
+
float* B,
|
359 |
+
size_t ldb);
|
360 |
+
|
361 |
+
cublasStatus_t CUBLASWINAPI cublasXtDtrsm(cublasXtHandle_t handle,
|
362 |
+
cublasSideMode_t side,
|
363 |
+
cublasFillMode_t uplo,
|
364 |
+
cublasOperation_t trans,
|
365 |
+
cublasDiagType_t diag,
|
366 |
+
size_t m,
|
367 |
+
size_t n,
|
368 |
+
const double* alpha,
|
369 |
+
const double* A,
|
370 |
+
size_t lda,
|
371 |
+
double* B,
|
372 |
+
size_t ldb);
|
373 |
+
|
374 |
+
cublasStatus_t CUBLASWINAPI cublasXtCtrsm(cublasXtHandle_t handle,
|
375 |
+
cublasSideMode_t side,
|
376 |
+
cublasFillMode_t uplo,
|
377 |
+
cublasOperation_t trans,
|
378 |
+
cublasDiagType_t diag,
|
379 |
+
size_t m,
|
380 |
+
size_t n,
|
381 |
+
const cuComplex* alpha,
|
382 |
+
const cuComplex* A,
|
383 |
+
size_t lda,
|
384 |
+
cuComplex* B,
|
385 |
+
size_t ldb);
|
386 |
+
|
387 |
+
cublasStatus_t CUBLASWINAPI cublasXtZtrsm(cublasXtHandle_t handle,
|
388 |
+
cublasSideMode_t side,
|
389 |
+
cublasFillMode_t uplo,
|
390 |
+
cublasOperation_t trans,
|
391 |
+
cublasDiagType_t diag,
|
392 |
+
size_t m,
|
393 |
+
size_t n,
|
394 |
+
const cuDoubleComplex* alpha,
|
395 |
+
const cuDoubleComplex* A,
|
396 |
+
size_t lda,
|
397 |
+
cuDoubleComplex* B,
|
398 |
+
size_t ldb);
|
399 |
+
/* -------------------------------------------------------------------- */
|
400 |
+
/* SYMM : Symmetric Multiply Matrix*/
|
401 |
+
cublasStatus_t CUBLASWINAPI cublasXtSsymm(cublasXtHandle_t handle,
|
402 |
+
cublasSideMode_t side,
|
403 |
+
cublasFillMode_t uplo,
|
404 |
+
size_t m,
|
405 |
+
size_t n,
|
406 |
+
const float* alpha,
|
407 |
+
const float* A,
|
408 |
+
size_t lda,
|
409 |
+
const float* B,
|
410 |
+
size_t ldb,
|
411 |
+
const float* beta,
|
412 |
+
float* C,
|
413 |
+
size_t ldc);
|
414 |
+
|
415 |
+
cublasStatus_t CUBLASWINAPI cublasXtDsymm(cublasXtHandle_t handle,
|
416 |
+
cublasSideMode_t side,
|
417 |
+
cublasFillMode_t uplo,
|
418 |
+
size_t m,
|
419 |
+
size_t n,
|
420 |
+
const double* alpha,
|
421 |
+
const double* A,
|
422 |
+
size_t lda,
|
423 |
+
const double* B,
|
424 |
+
size_t ldb,
|
425 |
+
const double* beta,
|
426 |
+
double* C,
|
427 |
+
size_t ldc);
|
428 |
+
|
429 |
+
cublasStatus_t CUBLASWINAPI cublasXtCsymm(cublasXtHandle_t handle,
|
430 |
+
cublasSideMode_t side,
|
431 |
+
cublasFillMode_t uplo,
|
432 |
+
size_t m,
|
433 |
+
size_t n,
|
434 |
+
const cuComplex* alpha,
|
435 |
+
const cuComplex* A,
|
436 |
+
size_t lda,
|
437 |
+
const cuComplex* B,
|
438 |
+
size_t ldb,
|
439 |
+
const cuComplex* beta,
|
440 |
+
cuComplex* C,
|
441 |
+
size_t ldc);
|
442 |
+
|
443 |
+
cublasStatus_t CUBLASWINAPI cublasXtZsymm(cublasXtHandle_t handle,
|
444 |
+
cublasSideMode_t side,
|
445 |
+
cublasFillMode_t uplo,
|
446 |
+
size_t m,
|
447 |
+
size_t n,
|
448 |
+
const cuDoubleComplex* alpha,
|
449 |
+
const cuDoubleComplex* A,
|
450 |
+
size_t lda,
|
451 |
+
const cuDoubleComplex* B,
|
452 |
+
size_t ldb,
|
453 |
+
const cuDoubleComplex* beta,
|
454 |
+
cuDoubleComplex* C,
|
455 |
+
size_t ldc);
|
456 |
+
/* -------------------------------------------------------------------- */
|
457 |
+
/* HEMM : Hermitian Matrix Multiply */
|
458 |
+
cublasStatus_t CUBLASWINAPI cublasXtChemm(cublasXtHandle_t handle,
|
459 |
+
cublasSideMode_t side,
|
460 |
+
cublasFillMode_t uplo,
|
461 |
+
size_t m,
|
462 |
+
size_t n,
|
463 |
+
const cuComplex* alpha,
|
464 |
+
const cuComplex* A,
|
465 |
+
size_t lda,
|
466 |
+
const cuComplex* B,
|
467 |
+
size_t ldb,
|
468 |
+
const cuComplex* beta,
|
469 |
+
cuComplex* C,
|
470 |
+
size_t ldc);
|
471 |
+
|
472 |
+
cublasStatus_t CUBLASWINAPI cublasXtZhemm(cublasXtHandle_t handle,
|
473 |
+
cublasSideMode_t side,
|
474 |
+
cublasFillMode_t uplo,
|
475 |
+
size_t m,
|
476 |
+
size_t n,
|
477 |
+
const cuDoubleComplex* alpha,
|
478 |
+
const cuDoubleComplex* A,
|
479 |
+
size_t lda,
|
480 |
+
const cuDoubleComplex* B,
|
481 |
+
size_t ldb,
|
482 |
+
const cuDoubleComplex* beta,
|
483 |
+
cuDoubleComplex* C,
|
484 |
+
size_t ldc);
|
485 |
+
|
486 |
+
/* -------------------------------------------------------------------- */
|
487 |
+
/* SYRKX : variant extension of SYRK */
|
488 |
+
cublasStatus_t CUBLASWINAPI cublasXtSsyrkx(cublasXtHandle_t handle,
|
489 |
+
cublasFillMode_t uplo,
|
490 |
+
cublasOperation_t trans,
|
491 |
+
size_t n,
|
492 |
+
size_t k,
|
493 |
+
const float* alpha,
|
494 |
+
const float* A,
|
495 |
+
size_t lda,
|
496 |
+
const float* B,
|
497 |
+
size_t ldb,
|
498 |
+
const float* beta,
|
499 |
+
float* C,
|
500 |
+
size_t ldc);
|
501 |
+
|
502 |
+
cublasStatus_t CUBLASWINAPI cublasXtDsyrkx(cublasXtHandle_t handle,
|
503 |
+
cublasFillMode_t uplo,
|
504 |
+
cublasOperation_t trans,
|
505 |
+
size_t n,
|
506 |
+
size_t k,
|
507 |
+
const double* alpha,
|
508 |
+
const double* A,
|
509 |
+
size_t lda,
|
510 |
+
const double* B,
|
511 |
+
size_t ldb,
|
512 |
+
const double* beta,
|
513 |
+
double* C,
|
514 |
+
size_t ldc);
|
515 |
+
|
516 |
+
cublasStatus_t CUBLASWINAPI cublasXtCsyrkx(cublasXtHandle_t handle,
|
517 |
+
cublasFillMode_t uplo,
|
518 |
+
cublasOperation_t trans,
|
519 |
+
size_t n,
|
520 |
+
size_t k,
|
521 |
+
const cuComplex* alpha,
|
522 |
+
const cuComplex* A,
|
523 |
+
size_t lda,
|
524 |
+
const cuComplex* B,
|
525 |
+
size_t ldb,
|
526 |
+
const cuComplex* beta,
|
527 |
+
cuComplex* C,
|
528 |
+
size_t ldc);
|
529 |
+
|
530 |
+
cublasStatus_t CUBLASWINAPI cublasXtZsyrkx(cublasXtHandle_t handle,
|
531 |
+
cublasFillMode_t uplo,
|
532 |
+
cublasOperation_t trans,
|
533 |
+
size_t n,
|
534 |
+
size_t k,
|
535 |
+
const cuDoubleComplex* alpha,
|
536 |
+
const cuDoubleComplex* A,
|
537 |
+
size_t lda,
|
538 |
+
const cuDoubleComplex* B,
|
539 |
+
size_t ldb,
|
540 |
+
const cuDoubleComplex* beta,
|
541 |
+
cuDoubleComplex* C,
|
542 |
+
size_t ldc);
|
543 |
+
/* -------------------------------------------------------------------- */
|
544 |
+
/* HER2K : variant extension of HERK */
|
545 |
+
cublasStatus_t CUBLASWINAPI cublasXtCher2k(cublasXtHandle_t handle,
|
546 |
+
cublasFillMode_t uplo,
|
547 |
+
cublasOperation_t trans,
|
548 |
+
size_t n,
|
549 |
+
size_t k,
|
550 |
+
const cuComplex* alpha,
|
551 |
+
const cuComplex* A,
|
552 |
+
size_t lda,
|
553 |
+
const cuComplex* B,
|
554 |
+
size_t ldb,
|
555 |
+
const float* beta,
|
556 |
+
cuComplex* C,
|
557 |
+
size_t ldc);
|
558 |
+
|
559 |
+
cublasStatus_t CUBLASWINAPI cublasXtZher2k(cublasXtHandle_t handle,
|
560 |
+
cublasFillMode_t uplo,
|
561 |
+
cublasOperation_t trans,
|
562 |
+
size_t n,
|
563 |
+
size_t k,
|
564 |
+
const cuDoubleComplex* alpha,
|
565 |
+
const cuDoubleComplex* A,
|
566 |
+
size_t lda,
|
567 |
+
const cuDoubleComplex* B,
|
568 |
+
size_t ldb,
|
569 |
+
const double* beta,
|
570 |
+
cuDoubleComplex* C,
|
571 |
+
size_t ldc);
|
572 |
+
|
573 |
+
/* -------------------------------------------------------------------- */
|
574 |
+
/* SPMM : Symmetric Packed Multiply Matrix*/
|
575 |
+
cublasStatus_t CUBLASWINAPI cublasXtSspmm(cublasXtHandle_t handle,
|
576 |
+
cublasSideMode_t side,
|
577 |
+
cublasFillMode_t uplo,
|
578 |
+
size_t m,
|
579 |
+
size_t n,
|
580 |
+
const float* alpha,
|
581 |
+
const float* AP,
|
582 |
+
const float* B,
|
583 |
+
size_t ldb,
|
584 |
+
const float* beta,
|
585 |
+
float* C,
|
586 |
+
size_t ldc);
|
587 |
+
|
588 |
+
cublasStatus_t CUBLASWINAPI cublasXtDspmm(cublasXtHandle_t handle,
|
589 |
+
cublasSideMode_t side,
|
590 |
+
cublasFillMode_t uplo,
|
591 |
+
size_t m,
|
592 |
+
size_t n,
|
593 |
+
const double* alpha,
|
594 |
+
const double* AP,
|
595 |
+
const double* B,
|
596 |
+
size_t ldb,
|
597 |
+
const double* beta,
|
598 |
+
double* C,
|
599 |
+
size_t ldc);
|
600 |
+
|
601 |
+
cublasStatus_t CUBLASWINAPI cublasXtCspmm(cublasXtHandle_t handle,
|
602 |
+
cublasSideMode_t side,
|
603 |
+
cublasFillMode_t uplo,
|
604 |
+
size_t m,
|
605 |
+
size_t n,
|
606 |
+
const cuComplex* alpha,
|
607 |
+
const cuComplex* AP,
|
608 |
+
const cuComplex* B,
|
609 |
+
size_t ldb,
|
610 |
+
const cuComplex* beta,
|
611 |
+
cuComplex* C,
|
612 |
+
size_t ldc);
|
613 |
+
|
614 |
+
cublasStatus_t CUBLASWINAPI cublasXtZspmm(cublasXtHandle_t handle,
|
615 |
+
cublasSideMode_t side,
|
616 |
+
cublasFillMode_t uplo,
|
617 |
+
size_t m,
|
618 |
+
size_t n,
|
619 |
+
const cuDoubleComplex* alpha,
|
620 |
+
const cuDoubleComplex* AP,
|
621 |
+
const cuDoubleComplex* B,
|
622 |
+
size_t ldb,
|
623 |
+
const cuDoubleComplex* beta,
|
624 |
+
cuDoubleComplex* C,
|
625 |
+
size_t ldc);
|
626 |
+
|
627 |
+
/* -------------------------------------------------------------------- */
|
628 |
+
/* TRMM */
|
629 |
+
cublasStatus_t CUBLASWINAPI cublasXtStrmm(cublasXtHandle_t handle,
|
630 |
+
cublasSideMode_t side,
|
631 |
+
cublasFillMode_t uplo,
|
632 |
+
cublasOperation_t trans,
|
633 |
+
cublasDiagType_t diag,
|
634 |
+
size_t m,
|
635 |
+
size_t n,
|
636 |
+
const float* alpha,
|
637 |
+
const float* A,
|
638 |
+
size_t lda,
|
639 |
+
const float* B,
|
640 |
+
size_t ldb,
|
641 |
+
float* C,
|
642 |
+
size_t ldc);
|
643 |
+
|
644 |
+
cublasStatus_t CUBLASWINAPI cublasXtDtrmm(cublasXtHandle_t handle,
|
645 |
+
cublasSideMode_t side,
|
646 |
+
cublasFillMode_t uplo,
|
647 |
+
cublasOperation_t trans,
|
648 |
+
cublasDiagType_t diag,
|
649 |
+
size_t m,
|
650 |
+
size_t n,
|
651 |
+
const double* alpha,
|
652 |
+
const double* A,
|
653 |
+
size_t lda,
|
654 |
+
const double* B,
|
655 |
+
size_t ldb,
|
656 |
+
double* C,
|
657 |
+
size_t ldc);
|
658 |
+
|
659 |
+
cublasStatus_t CUBLASWINAPI cublasXtCtrmm(cublasXtHandle_t handle,
|
660 |
+
cublasSideMode_t side,
|
661 |
+
cublasFillMode_t uplo,
|
662 |
+
cublasOperation_t trans,
|
663 |
+
cublasDiagType_t diag,
|
664 |
+
size_t m,
|
665 |
+
size_t n,
|
666 |
+
const cuComplex* alpha,
|
667 |
+
const cuComplex* A,
|
668 |
+
size_t lda,
|
669 |
+
const cuComplex* B,
|
670 |
+
size_t ldb,
|
671 |
+
cuComplex* C,
|
672 |
+
size_t ldc);
|
673 |
+
|
674 |
+
cublasStatus_t CUBLASWINAPI cublasXtZtrmm(cublasXtHandle_t handle,
|
675 |
+
cublasSideMode_t side,
|
676 |
+
cublasFillMode_t uplo,
|
677 |
+
cublasOperation_t trans,
|
678 |
+
cublasDiagType_t diag,
|
679 |
+
size_t m,
|
680 |
+
size_t n,
|
681 |
+
const cuDoubleComplex* alpha,
|
682 |
+
const cuDoubleComplex* A,
|
683 |
+
size_t lda,
|
684 |
+
const cuDoubleComplex* B,
|
685 |
+
size_t ldb,
|
686 |
+
cuDoubleComplex* C,
|
687 |
+
size_t ldc);
|
688 |
+
|
689 |
+
#if defined(__cplusplus)
|
690 |
+
}
|
691 |
+
#endif /* __cplusplus */
|
692 |
+
|
693 |
+
#endif /* !defined(CUBLAS_XT_H_) */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublas_api.h
ADDED
The diff for this file is too large to render.
See raw diff
|
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/cublas_v2.h
ADDED
@@ -0,0 +1,478 @@
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|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2019 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
/*
|
51 |
+
* This is the public header file for the new CUBLAS library API, it mapped the generic
|
52 |
+
* Cublas name functions to the actual _v2 implementations.
|
53 |
+
*/
|
54 |
+
|
55 |
+
#if !defined(CUBLAS_V2_H_)
|
56 |
+
#define CUBLAS_V2_H_
|
57 |
+
|
58 |
+
#if defined(CUBLAS_H_)
|
59 |
+
#error "It is an error to include both cublas.h and cublas_v2.h"
|
60 |
+
#endif
|
61 |
+
|
62 |
+
#undef CUBLASAPI
|
63 |
+
#ifdef __CUDACC__
|
64 |
+
#define CUBLASAPI __host__ __device__
|
65 |
+
#else
|
66 |
+
#define CUBLASAPI
|
67 |
+
#endif
|
68 |
+
|
69 |
+
#include "cublas_api.h"
|
70 |
+
|
71 |
+
#define cublasCreate cublasCreate_v2
|
72 |
+
#define cublasDestroy cublasDestroy_v2
|
73 |
+
#define cublasGetVersion cublasGetVersion_v2
|
74 |
+
#define cublasSetWorkspace cublasSetWorkspace_v2
|
75 |
+
#define cublasSetStream cublasSetStream_v2
|
76 |
+
#define cublasGetStream cublasGetStream_v2
|
77 |
+
#define cublasGetPointerMode cublasGetPointerMode_v2
|
78 |
+
#define cublasSetPointerMode cublasSetPointerMode_v2
|
79 |
+
|
80 |
+
/* 32-bit integer */
|
81 |
+
|
82 |
+
/* Blas1 Routines */
|
83 |
+
|
84 |
+
#define cublasSnrm2 cublasSnrm2_v2
|
85 |
+
#define cublasDnrm2 cublasDnrm2_v2
|
86 |
+
#define cublasScnrm2 cublasScnrm2_v2
|
87 |
+
#define cublasDznrm2 cublasDznrm2_v2
|
88 |
+
|
89 |
+
#define cublasSdot cublasSdot_v2
|
90 |
+
#define cublasDdot cublasDdot_v2
|
91 |
+
#define cublasCdotu cublasCdotu_v2
|
92 |
+
#define cublasCdotc cublasCdotc_v2
|
93 |
+
#define cublasZdotu cublasZdotu_v2
|
94 |
+
#define cublasZdotc cublasZdotc_v2
|
95 |
+
|
96 |
+
#define cublasSscal cublasSscal_v2
|
97 |
+
#define cublasDscal cublasDscal_v2
|
98 |
+
#define cublasCscal cublasCscal_v2
|
99 |
+
#define cublasCsscal cublasCsscal_v2
|
100 |
+
#define cublasZscal cublasZscal_v2
|
101 |
+
#define cublasZdscal cublasZdscal_v2
|
102 |
+
|
103 |
+
#define cublasSaxpy cublasSaxpy_v2
|
104 |
+
#define cublasDaxpy cublasDaxpy_v2
|
105 |
+
#define cublasCaxpy cublasCaxpy_v2
|
106 |
+
#define cublasZaxpy cublasZaxpy_v2
|
107 |
+
|
108 |
+
#define cublasScopy cublasScopy_v2
|
109 |
+
#define cublasDcopy cublasDcopy_v2
|
110 |
+
#define cublasCcopy cublasCcopy_v2
|
111 |
+
#define cublasZcopy cublasZcopy_v2
|
112 |
+
|
113 |
+
#define cublasSswap cublasSswap_v2
|
114 |
+
#define cublasDswap cublasDswap_v2
|
115 |
+
#define cublasCswap cublasCswap_v2
|
116 |
+
#define cublasZswap cublasZswap_v2
|
117 |
+
|
118 |
+
#define cublasIsamax cublasIsamax_v2
|
119 |
+
#define cublasIdamax cublasIdamax_v2
|
120 |
+
#define cublasIcamax cublasIcamax_v2
|
121 |
+
#define cublasIzamax cublasIzamax_v2
|
122 |
+
|
123 |
+
#define cublasIsamin cublasIsamin_v2
|
124 |
+
#define cublasIdamin cublasIdamin_v2
|
125 |
+
#define cublasIcamin cublasIcamin_v2
|
126 |
+
#define cublasIzamin cublasIzamin_v2
|
127 |
+
|
128 |
+
#define cublasSasum cublasSasum_v2
|
129 |
+
#define cublasDasum cublasDasum_v2
|
130 |
+
#define cublasScasum cublasScasum_v2
|
131 |
+
#define cublasDzasum cublasDzasum_v2
|
132 |
+
|
133 |
+
#define cublasSrot cublasSrot_v2
|
134 |
+
#define cublasDrot cublasDrot_v2
|
135 |
+
#define cublasCrot cublasCrot_v2
|
136 |
+
#define cublasCsrot cublasCsrot_v2
|
137 |
+
#define cublasZrot cublasZrot_v2
|
138 |
+
#define cublasZdrot cublasZdrot_v2
|
139 |
+
|
140 |
+
#define cublasSrotg cublasSrotg_v2
|
141 |
+
#define cublasDrotg cublasDrotg_v2
|
142 |
+
#define cublasCrotg cublasCrotg_v2
|
143 |
+
#define cublasZrotg cublasZrotg_v2
|
144 |
+
|
145 |
+
#define cublasSrotm cublasSrotm_v2
|
146 |
+
#define cublasDrotm cublasDrotm_v2
|
147 |
+
|
148 |
+
#define cublasSrotmg cublasSrotmg_v2
|
149 |
+
#define cublasDrotmg cublasDrotmg_v2
|
150 |
+
|
151 |
+
/* Blas2 Routines */
|
152 |
+
|
153 |
+
#define cublasSgemv cublasSgemv_v2
|
154 |
+
#define cublasDgemv cublasDgemv_v2
|
155 |
+
#define cublasCgemv cublasCgemv_v2
|
156 |
+
#define cublasZgemv cublasZgemv_v2
|
157 |
+
|
158 |
+
#define cublasSgbmv cublasSgbmv_v2
|
159 |
+
#define cublasDgbmv cublasDgbmv_v2
|
160 |
+
#define cublasCgbmv cublasCgbmv_v2
|
161 |
+
#define cublasZgbmv cublasZgbmv_v2
|
162 |
+
|
163 |
+
#define cublasStrmv cublasStrmv_v2
|
164 |
+
#define cublasDtrmv cublasDtrmv_v2
|
165 |
+
#define cublasCtrmv cublasCtrmv_v2
|
166 |
+
#define cublasZtrmv cublasZtrmv_v2
|
167 |
+
|
168 |
+
#define cublasStbmv cublasStbmv_v2
|
169 |
+
#define cublasDtbmv cublasDtbmv_v2
|
170 |
+
#define cublasCtbmv cublasCtbmv_v2
|
171 |
+
#define cublasZtbmv cublasZtbmv_v2
|
172 |
+
|
173 |
+
#define cublasStpmv cublasStpmv_v2
|
174 |
+
#define cublasDtpmv cublasDtpmv_v2
|
175 |
+
#define cublasCtpmv cublasCtpmv_v2
|
176 |
+
#define cublasZtpmv cublasZtpmv_v2
|
177 |
+
|
178 |
+
#define cublasStrsv cublasStrsv_v2
|
179 |
+
#define cublasDtrsv cublasDtrsv_v2
|
180 |
+
#define cublasCtrsv cublasCtrsv_v2
|
181 |
+
#define cublasZtrsv cublasZtrsv_v2
|
182 |
+
|
183 |
+
#define cublasStpsv cublasStpsv_v2
|
184 |
+
#define cublasDtpsv cublasDtpsv_v2
|
185 |
+
#define cublasCtpsv cublasCtpsv_v2
|
186 |
+
#define cublasZtpsv cublasZtpsv_v2
|
187 |
+
|
188 |
+
#define cublasStbsv cublasStbsv_v2
|
189 |
+
#define cublasDtbsv cublasDtbsv_v2
|
190 |
+
#define cublasCtbsv cublasCtbsv_v2
|
191 |
+
#define cublasZtbsv cublasZtbsv_v2
|
192 |
+
|
193 |
+
#define cublasSsymv cublasSsymv_v2
|
194 |
+
#define cublasDsymv cublasDsymv_v2
|
195 |
+
#define cublasCsymv cublasCsymv_v2
|
196 |
+
#define cublasZsymv cublasZsymv_v2
|
197 |
+
#define cublasChemv cublasChemv_v2
|
198 |
+
#define cublasZhemv cublasZhemv_v2
|
199 |
+
|
200 |
+
#define cublasSsbmv cublasSsbmv_v2
|
201 |
+
#define cublasDsbmv cublasDsbmv_v2
|
202 |
+
#define cublasChbmv cublasChbmv_v2
|
203 |
+
#define cublasZhbmv cublasZhbmv_v2
|
204 |
+
|
205 |
+
#define cublasSspmv cublasSspmv_v2
|
206 |
+
#define cublasDspmv cublasDspmv_v2
|
207 |
+
#define cublasChpmv cublasChpmv_v2
|
208 |
+
#define cublasZhpmv cublasZhpmv_v2
|
209 |
+
|
210 |
+
#define cublasSger cublasSger_v2
|
211 |
+
#define cublasDger cublasDger_v2
|
212 |
+
#define cublasCgeru cublasCgeru_v2
|
213 |
+
#define cublasCgerc cublasCgerc_v2
|
214 |
+
#define cublasZgeru cublasZgeru_v2
|
215 |
+
#define cublasZgerc cublasZgerc_v2
|
216 |
+
|
217 |
+
#define cublasSsyr cublasSsyr_v2
|
218 |
+
#define cublasDsyr cublasDsyr_v2
|
219 |
+
#define cublasCsyr cublasCsyr_v2
|
220 |
+
#define cublasZsyr cublasZsyr_v2
|
221 |
+
#define cublasCher cublasCher_v2
|
222 |
+
#define cublasZher cublasZher_v2
|
223 |
+
|
224 |
+
#define cublasSspr cublasSspr_v2
|
225 |
+
#define cublasDspr cublasDspr_v2
|
226 |
+
#define cublasChpr cublasChpr_v2
|
227 |
+
#define cublasZhpr cublasZhpr_v2
|
228 |
+
|
229 |
+
#define cublasSsyr2 cublasSsyr2_v2
|
230 |
+
#define cublasDsyr2 cublasDsyr2_v2
|
231 |
+
#define cublasCsyr2 cublasCsyr2_v2
|
232 |
+
#define cublasZsyr2 cublasZsyr2_v2
|
233 |
+
#define cublasCher2 cublasCher2_v2
|
234 |
+
#define cublasZher2 cublasZher2_v2
|
235 |
+
|
236 |
+
#define cublasSspr2 cublasSspr2_v2
|
237 |
+
#define cublasDspr2 cublasDspr2_v2
|
238 |
+
#define cublasChpr2 cublasChpr2_v2
|
239 |
+
#define cublasZhpr2 cublasZhpr2_v2
|
240 |
+
|
241 |
+
/* Blas3 Routines */
|
242 |
+
|
243 |
+
#define cublasSgemm cublasSgemm_v2
|
244 |
+
#define cublasDgemm cublasDgemm_v2
|
245 |
+
#define cublasCgemm cublasCgemm_v2
|
246 |
+
#define cublasZgemm cublasZgemm_v2
|
247 |
+
|
248 |
+
#define cublasSsyrk cublasSsyrk_v2
|
249 |
+
#define cublasDsyrk cublasDsyrk_v2
|
250 |
+
#define cublasCsyrk cublasCsyrk_v2
|
251 |
+
#define cublasZsyrk cublasZsyrk_v2
|
252 |
+
#define cublasCherk cublasCherk_v2
|
253 |
+
#define cublasZherk cublasZherk_v2
|
254 |
+
|
255 |
+
#define cublasSsyr2k cublasSsyr2k_v2
|
256 |
+
#define cublasDsyr2k cublasDsyr2k_v2
|
257 |
+
#define cublasCsyr2k cublasCsyr2k_v2
|
258 |
+
#define cublasZsyr2k cublasZsyr2k_v2
|
259 |
+
#define cublasCher2k cublasCher2k_v2
|
260 |
+
#define cublasZher2k cublasZher2k_v2
|
261 |
+
|
262 |
+
#define cublasSsymm cublasSsymm_v2
|
263 |
+
#define cublasDsymm cublasDsymm_v2
|
264 |
+
#define cublasCsymm cublasCsymm_v2
|
265 |
+
#define cublasZsymm cublasZsymm_v2
|
266 |
+
#define cublasChemm cublasChemm_v2
|
267 |
+
#define cublasZhemm cublasZhemm_v2
|
268 |
+
|
269 |
+
#define cublasStrsm cublasStrsm_v2
|
270 |
+
#define cublasDtrsm cublasDtrsm_v2
|
271 |
+
#define cublasCtrsm cublasCtrsm_v2
|
272 |
+
#define cublasZtrsm cublasZtrsm_v2
|
273 |
+
|
274 |
+
#define cublasStrmm cublasStrmm_v2
|
275 |
+
#define cublasDtrmm cublasDtrmm_v2
|
276 |
+
#define cublasCtrmm cublasCtrmm_v2
|
277 |
+
#define cublasZtrmm cublasZtrmm_v2
|
278 |
+
|
279 |
+
/* 64-bit integer */
|
280 |
+
|
281 |
+
/* Blas1 Routines */
|
282 |
+
|
283 |
+
#define cublasSnrm2_64 cublasSnrm2_v2_64
|
284 |
+
#define cublasDnrm2_64 cublasDnrm2_v2_64
|
285 |
+
#define cublasScnrm2_64 cublasScnrm2_v2_64
|
286 |
+
#define cublasDznrm2_64 cublasDznrm2_v2_64
|
287 |
+
|
288 |
+
#define cublasSdot_64 cublasSdot_v2_64
|
289 |
+
#define cublasDdot_64 cublasDdot_v2_64
|
290 |
+
#define cublasCdotu_64 cublasCdotu_v2_64
|
291 |
+
#define cublasCdotc_64 cublasCdotc_v2_64
|
292 |
+
#define cublasZdotu_64 cublasZdotu_v2_64
|
293 |
+
#define cublasZdotc_64 cublasZdotc_v2_64
|
294 |
+
|
295 |
+
#define cublasSscal_64 cublasSscal_v2_64
|
296 |
+
#define cublasDscal_64 cublasDscal_v2_64
|
297 |
+
#define cublasCscal_64 cublasCscal_v2_64
|
298 |
+
#define cublasCsscal_64 cublasCsscal_v2_64
|
299 |
+
#define cublasZscal_64 cublasZscal_v2_64
|
300 |
+
#define cublasZdscal_64 cublasZdscal_v2_64
|
301 |
+
|
302 |
+
#define cublasSaxpy_64 cublasSaxpy_v2_64
|
303 |
+
#define cublasDaxpy_64 cublasDaxpy_v2_64
|
304 |
+
#define cublasCaxpy_64 cublasCaxpy_v2_64
|
305 |
+
#define cublasZaxpy_64 cublasZaxpy_v2_64
|
306 |
+
|
307 |
+
#define cublasScopy_64 cublasScopy_v2_64
|
308 |
+
#define cublasDcopy_64 cublasDcopy_v2_64
|
309 |
+
#define cublasCcopy_64 cublasCcopy_v2_64
|
310 |
+
#define cublasZcopy_64 cublasZcopy_v2_64
|
311 |
+
|
312 |
+
#define cublasSswap_64 cublasSswap_v2_64
|
313 |
+
#define cublasDswap_64 cublasDswap_v2_64
|
314 |
+
#define cublasCswap_64 cublasCswap_v2_64
|
315 |
+
#define cublasZswap_64 cublasZswap_v2_64
|
316 |
+
|
317 |
+
#define cublasIsamax_64 cublasIsamax_v2_64
|
318 |
+
#define cublasIdamax_64 cublasIdamax_v2_64
|
319 |
+
#define cublasIcamax_64 cublasIcamax_v2_64
|
320 |
+
#define cublasIzamax_64 cublasIzamax_v2_64
|
321 |
+
|
322 |
+
#define cublasIsamin_64 cublasIsamin_v2_64
|
323 |
+
#define cublasIdamin_64 cublasIdamin_v2_64
|
324 |
+
#define cublasIcamin_64 cublasIcamin_v2_64
|
325 |
+
#define cublasIzamin_64 cublasIzamin_v2_64
|
326 |
+
|
327 |
+
#define cublasSasum_64 cublasSasum_v2_64
|
328 |
+
#define cublasDasum_64 cublasDasum_v2_64
|
329 |
+
#define cublasScasum_64 cublasScasum_v2_64
|
330 |
+
#define cublasDzasum_64 cublasDzasum_v2_64
|
331 |
+
|
332 |
+
#define cublasSrot_64 cublasSrot_v2_64
|
333 |
+
#define cublasDrot_64 cublasDrot_v2_64
|
334 |
+
#define cublasCrot_64 cublasCrot_v2_64
|
335 |
+
#define cublasCsrot_64 cublasCsrot_v2_64
|
336 |
+
#define cublasZrot_64 cublasZrot_v2_64
|
337 |
+
#define cublasZdrot_64 cublasZdrot_v2_64
|
338 |
+
|
339 |
+
#define cublasSrotg_64 cublasSrotg_v2_64
|
340 |
+
#define cublasDrotg_64 cublasDrotg_v2_64
|
341 |
+
#define cublasCrotg_64 cublasCrotg_v2_64
|
342 |
+
#define cublasZrotg_64 cublasZrotg_v2_64
|
343 |
+
|
344 |
+
#define cublasSrotm_64 cublasSrotm_v2_64
|
345 |
+
#define cublasDrotm_64 cublasDrotm_v2_64
|
346 |
+
|
347 |
+
#define cublasSrotmg_64 cublasSrotmg_v2_64
|
348 |
+
#define cublasDrotmg_64 cublasDrotmg_v2_64
|
349 |
+
|
350 |
+
/* Blas2 Routines */
|
351 |
+
|
352 |
+
#define cublasSgemv_64 cublasSgemv_v2_64
|
353 |
+
#define cublasDgemv_64 cublasDgemv_v2_64
|
354 |
+
#define cublasCgemv_64 cublasCgemv_v2_64
|
355 |
+
#define cublasZgemv_64 cublasZgemv_v2_64
|
356 |
+
|
357 |
+
#define cublasSgbmv_64 cublasSgbmv_v2_64
|
358 |
+
#define cublasDgbmv_64 cublasDgbmv_v2_64
|
359 |
+
#define cublasCgbmv_64 cublasCgbmv_v2_64
|
360 |
+
#define cublasZgbmv_64 cublasZgbmv_v2_64
|
361 |
+
|
362 |
+
#define cublasStrmv_64 cublasStrmv_v2_64
|
363 |
+
#define cublasDtrmv_64 cublasDtrmv_v2_64
|
364 |
+
#define cublasCtrmv_64 cublasCtrmv_v2_64
|
365 |
+
#define cublasZtrmv_64 cublasZtrmv_v2_64
|
366 |
+
|
367 |
+
#define cublasStbmv_64 cublasStbmv_v2_64
|
368 |
+
#define cublasDtbmv_64 cublasDtbmv_v2_64
|
369 |
+
#define cublasCtbmv_64 cublasCtbmv_v2_64
|
370 |
+
#define cublasZtbmv_64 cublasZtbmv_v2_64
|
371 |
+
|
372 |
+
#define cublasStpmv_64 cublasStpmv_v2_64
|
373 |
+
#define cublasDtpmv_64 cublasDtpmv_v2_64
|
374 |
+
#define cublasCtpmv_64 cublasCtpmv_v2_64
|
375 |
+
#define cublasZtpmv_64 cublasZtpmv_v2_64
|
376 |
+
|
377 |
+
#define cublasStrsv_64 cublasStrsv_v2_64
|
378 |
+
#define cublasDtrsv_64 cublasDtrsv_v2_64
|
379 |
+
#define cublasCtrsv_64 cublasCtrsv_v2_64
|
380 |
+
#define cublasZtrsv_64 cublasZtrsv_v2_64
|
381 |
+
|
382 |
+
#define cublasStpsv_64 cublasStpsv_v2_64
|
383 |
+
#define cublasDtpsv_64 cublasDtpsv_v2_64
|
384 |
+
#define cublasCtpsv_64 cublasCtpsv_v2_64
|
385 |
+
#define cublasZtpsv_64 cublasZtpsv_v2_64
|
386 |
+
|
387 |
+
#define cublasStbsv_64 cublasStbsv_v2_64
|
388 |
+
#define cublasDtbsv_64 cublasDtbsv_v2_64
|
389 |
+
#define cublasCtbsv_64 cublasCtbsv_v2_64
|
390 |
+
#define cublasZtbsv_64 cublasZtbsv_v2_64
|
391 |
+
|
392 |
+
#define cublasSsymv_64 cublasSsymv_v2_64
|
393 |
+
#define cublasDsymv_64 cublasDsymv_v2_64
|
394 |
+
#define cublasCsymv_64 cublasCsymv_v2_64
|
395 |
+
#define cublasZsymv_64 cublasZsymv_v2_64
|
396 |
+
#define cublasChemv_64 cublasChemv_v2_64
|
397 |
+
#define cublasZhemv_64 cublasZhemv_v2_64
|
398 |
+
|
399 |
+
#define cublasSsbmv_64 cublasSsbmv_v2_64
|
400 |
+
#define cublasDsbmv_64 cublasDsbmv_v2_64
|
401 |
+
#define cublasChbmv_64 cublasChbmv_v2_64
|
402 |
+
#define cublasZhbmv_64 cublasZhbmv_v2_64
|
403 |
+
|
404 |
+
#define cublasSspmv_64 cublasSspmv_v2_64
|
405 |
+
#define cublasDspmv_64 cublasDspmv_v2_64
|
406 |
+
#define cublasChpmv_64 cublasChpmv_v2_64
|
407 |
+
#define cublasZhpmv_64 cublasZhpmv_v2_64
|
408 |
+
|
409 |
+
#define cublasSger_64 cublasSger_v2_64
|
410 |
+
#define cublasDger_64 cublasDger_v2_64
|
411 |
+
#define cublasCgeru_64 cublasCgeru_v2_64
|
412 |
+
#define cublasCgerc_64 cublasCgerc_v2_64
|
413 |
+
#define cublasZgeru_64 cublasZgeru_v2_64
|
414 |
+
#define cublasZgerc_64 cublasZgerc_v2_64
|
415 |
+
|
416 |
+
#define cublasSsyr_64 cublasSsyr_v2_64
|
417 |
+
#define cublasDsyr_64 cublasDsyr_v2_64
|
418 |
+
#define cublasCsyr_64 cublasCsyr_v2_64
|
419 |
+
#define cublasZsyr_64 cublasZsyr_v2_64
|
420 |
+
#define cublasCher_64 cublasCher_v2_64
|
421 |
+
#define cublasZher_64 cublasZher_v2_64
|
422 |
+
|
423 |
+
#define cublasSspr_64 cublasSspr_v2_64
|
424 |
+
#define cublasDspr_64 cublasDspr_v2_64
|
425 |
+
#define cublasChpr_64 cublasChpr_v2_64
|
426 |
+
#define cublasZhpr_64 cublasZhpr_v2_64
|
427 |
+
|
428 |
+
#define cublasSsyr2_64 cublasSsyr2_v2_64
|
429 |
+
#define cublasDsyr2_64 cublasDsyr2_v2_64
|
430 |
+
#define cublasCsyr2_64 cublasCsyr2_v2_64
|
431 |
+
#define cublasZsyr2_64 cublasZsyr2_v2_64
|
432 |
+
#define cublasCher2_64 cublasCher2_v2_64
|
433 |
+
#define cublasZher2_64 cublasZher2_v2_64
|
434 |
+
|
435 |
+
#define cublasSspr2_64 cublasSspr2_v2_64
|
436 |
+
#define cublasDspr2_64 cublasDspr2_v2_64
|
437 |
+
#define cublasChpr2_64 cublasChpr2_v2_64
|
438 |
+
#define cublasZhpr2_64 cublasZhpr2_v2_64
|
439 |
+
|
440 |
+
/* Blas3 Routines */
|
441 |
+
|
442 |
+
#define cublasSgemm_64 cublasSgemm_v2_64
|
443 |
+
#define cublasDgemm_64 cublasDgemm_v2_64
|
444 |
+
#define cublasCgemm_64 cublasCgemm_v2_64
|
445 |
+
#define cublasZgemm_64 cublasZgemm_v2_64
|
446 |
+
|
447 |
+
#define cublasSsyrk_64 cublasSsyrk_v2_64
|
448 |
+
#define cublasDsyrk_64 cublasDsyrk_v2_64
|
449 |
+
#define cublasCsyrk_64 cublasCsyrk_v2_64
|
450 |
+
#define cublasZsyrk_64 cublasZsyrk_v2_64
|
451 |
+
#define cublasCherk_64 cublasCherk_v2_64
|
452 |
+
#define cublasZherk_64 cublasZherk_v2_64
|
453 |
+
|
454 |
+
#define cublasSsyr2k_64 cublasSsyr2k_v2_64
|
455 |
+
#define cublasDsyr2k_64 cublasDsyr2k_v2_64
|
456 |
+
#define cublasCsyr2k_64 cublasCsyr2k_v2_64
|
457 |
+
#define cublasZsyr2k_64 cublasZsyr2k_v2_64
|
458 |
+
#define cublasCher2k_64 cublasCher2k_v2_64
|
459 |
+
#define cublasZher2k_64 cublasZher2k_v2_64
|
460 |
+
|
461 |
+
#define cublasSsymm_64 cublasSsymm_v2_64
|
462 |
+
#define cublasDsymm_64 cublasDsymm_v2_64
|
463 |
+
#define cublasCsymm_64 cublasCsymm_v2_64
|
464 |
+
#define cublasZsymm_64 cublasZsymm_v2_64
|
465 |
+
#define cublasChemm_64 cublasChemm_v2_64
|
466 |
+
#define cublasZhemm_64 cublasZhemm_v2_64
|
467 |
+
|
468 |
+
#define cublasStrsm_64 cublasStrsm_v2_64
|
469 |
+
#define cublasDtrsm_64 cublasDtrsm_v2_64
|
470 |
+
#define cublasCtrsm_64 cublasCtrsm_v2_64
|
471 |
+
#define cublasZtrsm_64 cublasZtrsm_v2_64
|
472 |
+
|
473 |
+
#define cublasStrmm_64 cublasStrmm_v2_64
|
474 |
+
#define cublasDtrmm_64 cublasDtrmm_v2_64
|
475 |
+
#define cublasCtrmm_64 cublasCtrmm_v2_64
|
476 |
+
#define cublasZtrmm_64 cublasZtrmm_v2_64
|
477 |
+
|
478 |
+
#endif /* !defined(CUBLAS_V2_H_) */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/include/nvblas.h
ADDED
@@ -0,0 +1,824 @@
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|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2019 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(NVBLAS_H_)
|
51 |
+
#define NVBLAS_H_
|
52 |
+
|
53 |
+
#include "driver_types.h"
|
54 |
+
#include "cuComplex.h" /* import complex data type */
|
55 |
+
|
56 |
+
#if defined(__cplusplus)
|
57 |
+
extern "C" {
|
58 |
+
#endif
|
59 |
+
|
60 |
+
/* GEMM */
|
61 |
+
void sgemm_(const char* transa,
|
62 |
+
const char* transb,
|
63 |
+
const int* m,
|
64 |
+
const int* n,
|
65 |
+
const int* k,
|
66 |
+
const float* alpha,
|
67 |
+
const float* a,
|
68 |
+
const int* lda,
|
69 |
+
const float* b,
|
70 |
+
const int* ldb,
|
71 |
+
const float* beta,
|
72 |
+
float* c,
|
73 |
+
const int* ldc);
|
74 |
+
|
75 |
+
void dgemm_(const char* transa,
|
76 |
+
const char* transb,
|
77 |
+
const int* m,
|
78 |
+
const int* n,
|
79 |
+
const int* k,
|
80 |
+
const double* alpha,
|
81 |
+
const double* a,
|
82 |
+
const int* lda,
|
83 |
+
const double* b,
|
84 |
+
const int* ldb,
|
85 |
+
const double* beta,
|
86 |
+
double* c,
|
87 |
+
const int* ldc);
|
88 |
+
|
89 |
+
void cgemm_(const char* transa,
|
90 |
+
const char* transb,
|
91 |
+
const int* m,
|
92 |
+
const int* n,
|
93 |
+
const int* k,
|
94 |
+
const cuComplex* alpha,
|
95 |
+
const cuComplex* a,
|
96 |
+
const int* lda,
|
97 |
+
const cuComplex* b,
|
98 |
+
const int* ldb,
|
99 |
+
const cuComplex* beta,
|
100 |
+
cuComplex* c,
|
101 |
+
const int* ldc);
|
102 |
+
|
103 |
+
void zgemm_(const char* transa,
|
104 |
+
const char* transb,
|
105 |
+
const int* m,
|
106 |
+
const int* n,
|
107 |
+
const int* k,
|
108 |
+
const cuDoubleComplex* alpha,
|
109 |
+
const cuDoubleComplex* a,
|
110 |
+
const int* lda,
|
111 |
+
const cuDoubleComplex* b,
|
112 |
+
const int* ldb,
|
113 |
+
const cuDoubleComplex* beta,
|
114 |
+
cuDoubleComplex* c,
|
115 |
+
const int* ldc);
|
116 |
+
|
117 |
+
void sgemm(const char* transa,
|
118 |
+
const char* transb,
|
119 |
+
const int* m,
|
120 |
+
const int* n,
|
121 |
+
const int* k,
|
122 |
+
const float* alpha,
|
123 |
+
const float* a,
|
124 |
+
const int* lda,
|
125 |
+
const float* b,
|
126 |
+
const int* ldb,
|
127 |
+
const float* beta,
|
128 |
+
float* c,
|
129 |
+
const int* ldc);
|
130 |
+
|
131 |
+
void dgemm(const char* transa,
|
132 |
+
const char* transb,
|
133 |
+
const int* m,
|
134 |
+
const int* n,
|
135 |
+
const int* k,
|
136 |
+
const double* alpha,
|
137 |
+
const double* a,
|
138 |
+
const int* lda,
|
139 |
+
const double* b,
|
140 |
+
const int* ldb,
|
141 |
+
const double* beta,
|
142 |
+
double* c,
|
143 |
+
const int* ldc);
|
144 |
+
|
145 |
+
void cgemm(const char* transa,
|
146 |
+
const char* transb,
|
147 |
+
const int* m,
|
148 |
+
const int* n,
|
149 |
+
const int* k,
|
150 |
+
const cuComplex* alpha,
|
151 |
+
const cuComplex* a,
|
152 |
+
const int* lda,
|
153 |
+
const cuComplex* b,
|
154 |
+
const int* ldb,
|
155 |
+
const cuComplex* beta,
|
156 |
+
cuComplex* c,
|
157 |
+
const int* ldc);
|
158 |
+
|
159 |
+
void zgemm(const char* transa,
|
160 |
+
const char* transb,
|
161 |
+
const int* m,
|
162 |
+
const int* n,
|
163 |
+
const int* k,
|
164 |
+
const cuDoubleComplex* alpha,
|
165 |
+
const cuDoubleComplex* a,
|
166 |
+
const int* lda,
|
167 |
+
const cuDoubleComplex* b,
|
168 |
+
const int* ldb,
|
169 |
+
const cuDoubleComplex* beta,
|
170 |
+
cuDoubleComplex* c,
|
171 |
+
const int* ldc);
|
172 |
+
|
173 |
+
/* SYRK */
|
174 |
+
void ssyrk_(const char* uplo,
|
175 |
+
const char* trans,
|
176 |
+
const int* n,
|
177 |
+
const int* k,
|
178 |
+
const float* alpha,
|
179 |
+
const float* a,
|
180 |
+
const int* lda,
|
181 |
+
const float* beta,
|
182 |
+
float* c,
|
183 |
+
const int* ldc);
|
184 |
+
|
185 |
+
void dsyrk_(const char* uplo,
|
186 |
+
const char* trans,
|
187 |
+
const int* n,
|
188 |
+
const int* k,
|
189 |
+
const double* alpha,
|
190 |
+
const double* a,
|
191 |
+
const int* lda,
|
192 |
+
const double* beta,
|
193 |
+
double* c,
|
194 |
+
const int* ldc);
|
195 |
+
|
196 |
+
void csyrk_(const char* uplo,
|
197 |
+
const char* trans,
|
198 |
+
const int* n,
|
199 |
+
const int* k,
|
200 |
+
const cuComplex* alpha,
|
201 |
+
const cuComplex* a,
|
202 |
+
const int* lda,
|
203 |
+
const cuComplex* beta,
|
204 |
+
cuComplex* c,
|
205 |
+
const int* ldc);
|
206 |
+
|
207 |
+
void zsyrk_(const char* uplo,
|
208 |
+
const char* trans,
|
209 |
+
const int* n,
|
210 |
+
const int* k,
|
211 |
+
const cuDoubleComplex* alpha,
|
212 |
+
const cuDoubleComplex* a,
|
213 |
+
const int* lda,
|
214 |
+
const cuDoubleComplex* beta,
|
215 |
+
cuDoubleComplex* c,
|
216 |
+
const int* ldc);
|
217 |
+
|
218 |
+
void ssyrk(const char* uplo,
|
219 |
+
const char* trans,
|
220 |
+
const int* n,
|
221 |
+
const int* k,
|
222 |
+
const float* alpha,
|
223 |
+
const float* a,
|
224 |
+
const int* lda,
|
225 |
+
const float* beta,
|
226 |
+
float* c,
|
227 |
+
const int* ldc);
|
228 |
+
|
229 |
+
void dsyrk(const char* uplo,
|
230 |
+
const char* trans,
|
231 |
+
const int* n,
|
232 |
+
const int* k,
|
233 |
+
const double* alpha,
|
234 |
+
const double* a,
|
235 |
+
const int* lda,
|
236 |
+
const double* beta,
|
237 |
+
double* c,
|
238 |
+
const int* ldc);
|
239 |
+
|
240 |
+
void csyrk(const char* uplo,
|
241 |
+
const char* trans,
|
242 |
+
const int* n,
|
243 |
+
const int* k,
|
244 |
+
const cuComplex* alpha,
|
245 |
+
const cuComplex* a,
|
246 |
+
const int* lda,
|
247 |
+
const cuComplex* beta,
|
248 |
+
cuComplex* c,
|
249 |
+
const int* ldc);
|
250 |
+
|
251 |
+
void zsyrk(const char* uplo,
|
252 |
+
const char* trans,
|
253 |
+
const int* n,
|
254 |
+
const int* k,
|
255 |
+
const cuDoubleComplex* alpha,
|
256 |
+
const cuDoubleComplex* a,
|
257 |
+
const int* lda,
|
258 |
+
const cuDoubleComplex* beta,
|
259 |
+
cuDoubleComplex* c,
|
260 |
+
const int* ldc);
|
261 |
+
|
262 |
+
/* HERK */
|
263 |
+
void cherk_(const char* uplo,
|
264 |
+
const char* trans,
|
265 |
+
const int* n,
|
266 |
+
const int* k,
|
267 |
+
const float* alpha,
|
268 |
+
const cuComplex* a,
|
269 |
+
const int* lda,
|
270 |
+
const float* beta,
|
271 |
+
cuComplex* c,
|
272 |
+
const int* ldc);
|
273 |
+
|
274 |
+
void zherk_(const char* uplo,
|
275 |
+
const char* trans,
|
276 |
+
const int* n,
|
277 |
+
const int* k,
|
278 |
+
const double* alpha,
|
279 |
+
const cuDoubleComplex* a,
|
280 |
+
const int* lda,
|
281 |
+
const double* beta,
|
282 |
+
cuDoubleComplex* c,
|
283 |
+
const int* ldc);
|
284 |
+
|
285 |
+
void cherk(const char* uplo,
|
286 |
+
const char* trans,
|
287 |
+
const int* n,
|
288 |
+
const int* k,
|
289 |
+
const float* alpha,
|
290 |
+
const cuComplex* a,
|
291 |
+
const int* lda,
|
292 |
+
const float* beta,
|
293 |
+
cuComplex* c,
|
294 |
+
const int* ldc);
|
295 |
+
|
296 |
+
void zherk(const char* uplo,
|
297 |
+
const char* trans,
|
298 |
+
const int* n,
|
299 |
+
const int* k,
|
300 |
+
const double* alpha,
|
301 |
+
const cuDoubleComplex* a,
|
302 |
+
const int* lda,
|
303 |
+
const double* beta,
|
304 |
+
cuDoubleComplex* c,
|
305 |
+
const int* ldc);
|
306 |
+
|
307 |
+
/* TRSM */
|
308 |
+
void strsm_(const char* side,
|
309 |
+
const char* uplo,
|
310 |
+
const char* transa,
|
311 |
+
const char* diag,
|
312 |
+
const int* m,
|
313 |
+
const int* n,
|
314 |
+
const float* alpha,
|
315 |
+
const float* a,
|
316 |
+
const int* lda,
|
317 |
+
float* b,
|
318 |
+
const int* ldb);
|
319 |
+
|
320 |
+
void dtrsm_(const char* side,
|
321 |
+
const char* uplo,
|
322 |
+
const char* transa,
|
323 |
+
const char* diag,
|
324 |
+
const int* m,
|
325 |
+
const int* n,
|
326 |
+
const double* alpha,
|
327 |
+
const double* a,
|
328 |
+
const int* lda,
|
329 |
+
double* b,
|
330 |
+
const int* ldb);
|
331 |
+
|
332 |
+
void ctrsm_(const char* side,
|
333 |
+
const char* uplo,
|
334 |
+
const char* transa,
|
335 |
+
const char* diag,
|
336 |
+
const int* m,
|
337 |
+
const int* n,
|
338 |
+
const cuComplex* alpha,
|
339 |
+
const cuComplex* a,
|
340 |
+
const int* lda,
|
341 |
+
cuComplex* b,
|
342 |
+
const int* ldb);
|
343 |
+
|
344 |
+
void ztrsm_(const char* side,
|
345 |
+
const char* uplo,
|
346 |
+
const char* transa,
|
347 |
+
const char* diag,
|
348 |
+
const int* m,
|
349 |
+
const int* n,
|
350 |
+
const cuDoubleComplex* alpha,
|
351 |
+
const cuDoubleComplex* a,
|
352 |
+
const int* lda,
|
353 |
+
cuDoubleComplex* b,
|
354 |
+
const int* ldb);
|
355 |
+
|
356 |
+
void strsm(const char* side,
|
357 |
+
const char* uplo,
|
358 |
+
const char* transa,
|
359 |
+
const char* diag,
|
360 |
+
const int* m,
|
361 |
+
const int* n,
|
362 |
+
const float* alpha,
|
363 |
+
const float* a,
|
364 |
+
const int* lda,
|
365 |
+
float* b,
|
366 |
+
const int* ldb);
|
367 |
+
|
368 |
+
void dtrsm(const char* side,
|
369 |
+
const char* uplo,
|
370 |
+
const char* transa,
|
371 |
+
const char* diag,
|
372 |
+
const int* m,
|
373 |
+
const int* n,
|
374 |
+
const double* alpha,
|
375 |
+
const double* a,
|
376 |
+
const int* lda,
|
377 |
+
double* b,
|
378 |
+
const int* ldb);
|
379 |
+
|
380 |
+
void ctrsm(const char* side,
|
381 |
+
const char* uplo,
|
382 |
+
const char* transa,
|
383 |
+
const char* diag,
|
384 |
+
const int* m,
|
385 |
+
const int* n,
|
386 |
+
const cuComplex* alpha,
|
387 |
+
const cuComplex* a,
|
388 |
+
const int* lda,
|
389 |
+
cuComplex* b,
|
390 |
+
const int* ldb);
|
391 |
+
|
392 |
+
void ztrsm(const char* side,
|
393 |
+
const char* uplo,
|
394 |
+
const char* transa,
|
395 |
+
const char* diag,
|
396 |
+
const int* m,
|
397 |
+
const int* n,
|
398 |
+
const cuDoubleComplex* alpha,
|
399 |
+
const cuDoubleComplex* a,
|
400 |
+
const int* lda,
|
401 |
+
cuDoubleComplex* b,
|
402 |
+
const int* ldb);
|
403 |
+
|
404 |
+
/* SYMM */
|
405 |
+
void ssymm_(const char* side,
|
406 |
+
const char* uplo,
|
407 |
+
const int* m,
|
408 |
+
const int* n,
|
409 |
+
const float* alpha,
|
410 |
+
const float* a,
|
411 |
+
const int* lda,
|
412 |
+
const float* b,
|
413 |
+
const int* ldb,
|
414 |
+
const float* beta,
|
415 |
+
float* c,
|
416 |
+
const int* ldc);
|
417 |
+
|
418 |
+
void dsymm_(const char* side,
|
419 |
+
const char* uplo,
|
420 |
+
const int* m,
|
421 |
+
const int* n,
|
422 |
+
const double* alpha,
|
423 |
+
const double* a,
|
424 |
+
const int* lda,
|
425 |
+
const double* b,
|
426 |
+
const int* ldb,
|
427 |
+
const double* beta,
|
428 |
+
double* c,
|
429 |
+
const int* ldc);
|
430 |
+
|
431 |
+
void csymm_(const char* side,
|
432 |
+
const char* uplo,
|
433 |
+
const int* m,
|
434 |
+
const int* n,
|
435 |
+
const cuComplex* alpha,
|
436 |
+
const cuComplex* a,
|
437 |
+
const int* lda,
|
438 |
+
const cuComplex* b,
|
439 |
+
const int* ldb,
|
440 |
+
const cuComplex* beta,
|
441 |
+
cuComplex* c,
|
442 |
+
const int* ldc);
|
443 |
+
|
444 |
+
void zsymm_(const char* side,
|
445 |
+
const char* uplo,
|
446 |
+
const int* m,
|
447 |
+
const int* n,
|
448 |
+
const cuDoubleComplex* alpha,
|
449 |
+
const cuDoubleComplex* a,
|
450 |
+
const int* lda,
|
451 |
+
const cuDoubleComplex* b,
|
452 |
+
const int* ldb,
|
453 |
+
const cuDoubleComplex* beta,
|
454 |
+
cuDoubleComplex* c,
|
455 |
+
const int* ldc);
|
456 |
+
|
457 |
+
void ssymm(const char* side,
|
458 |
+
const char* uplo,
|
459 |
+
const int* m,
|
460 |
+
const int* n,
|
461 |
+
const float* alpha,
|
462 |
+
const float* a,
|
463 |
+
const int* lda,
|
464 |
+
const float* b,
|
465 |
+
const int* ldb,
|
466 |
+
const float* beta,
|
467 |
+
float* c,
|
468 |
+
const int* ldc);
|
469 |
+
|
470 |
+
void dsymm(const char* side,
|
471 |
+
const char* uplo,
|
472 |
+
const int* m,
|
473 |
+
const int* n,
|
474 |
+
const double* alpha,
|
475 |
+
const double* a,
|
476 |
+
const int* lda,
|
477 |
+
const double* b,
|
478 |
+
const int* ldb,
|
479 |
+
const double* beta,
|
480 |
+
double* c,
|
481 |
+
const int* ldc);
|
482 |
+
|
483 |
+
void csymm(const char* side,
|
484 |
+
const char* uplo,
|
485 |
+
const int* m,
|
486 |
+
const int* n,
|
487 |
+
const cuComplex* alpha,
|
488 |
+
const cuComplex* a,
|
489 |
+
const int* lda,
|
490 |
+
const cuComplex* b,
|
491 |
+
const int* ldb,
|
492 |
+
const cuComplex* beta,
|
493 |
+
cuComplex* c,
|
494 |
+
const int* ldc);
|
495 |
+
|
496 |
+
void zsymm(const char* side,
|
497 |
+
const char* uplo,
|
498 |
+
const int* m,
|
499 |
+
const int* n,
|
500 |
+
const cuDoubleComplex* alpha,
|
501 |
+
const cuDoubleComplex* a,
|
502 |
+
const int* lda,
|
503 |
+
const cuDoubleComplex* b,
|
504 |
+
const int* ldb,
|
505 |
+
const cuDoubleComplex* beta,
|
506 |
+
cuDoubleComplex* c,
|
507 |
+
const int* ldc);
|
508 |
+
|
509 |
+
/* HEMM */
|
510 |
+
void chemm_(const char* side,
|
511 |
+
const char* uplo,
|
512 |
+
const int* m,
|
513 |
+
const int* n,
|
514 |
+
const cuComplex* alpha,
|
515 |
+
const cuComplex* a,
|
516 |
+
const int* lda,
|
517 |
+
const cuComplex* b,
|
518 |
+
const int* ldb,
|
519 |
+
const cuComplex* beta,
|
520 |
+
cuComplex* c,
|
521 |
+
const int* ldc);
|
522 |
+
|
523 |
+
void zhemm_(const char* side,
|
524 |
+
const char* uplo,
|
525 |
+
const int* m,
|
526 |
+
const int* n,
|
527 |
+
const cuDoubleComplex* alpha,
|
528 |
+
const cuDoubleComplex* a,
|
529 |
+
const int* lda,
|
530 |
+
const cuDoubleComplex* b,
|
531 |
+
const int* ldb,
|
532 |
+
const cuDoubleComplex* beta,
|
533 |
+
cuDoubleComplex* c,
|
534 |
+
const int* ldc);
|
535 |
+
|
536 |
+
/* HEMM with no underscore*/
|
537 |
+
void chemm(const char* side,
|
538 |
+
const char* uplo,
|
539 |
+
const int* m,
|
540 |
+
const int* n,
|
541 |
+
const cuComplex* alpha,
|
542 |
+
const cuComplex* a,
|
543 |
+
const int* lda,
|
544 |
+
const cuComplex* b,
|
545 |
+
const int* ldb,
|
546 |
+
const cuComplex* beta,
|
547 |
+
cuComplex* c,
|
548 |
+
const int* ldc);
|
549 |
+
|
550 |
+
void zhemm(const char* side,
|
551 |
+
const char* uplo,
|
552 |
+
const int* m,
|
553 |
+
const int* n,
|
554 |
+
const cuDoubleComplex* alpha,
|
555 |
+
const cuDoubleComplex* a,
|
556 |
+
const int* lda,
|
557 |
+
const cuDoubleComplex* b,
|
558 |
+
const int* ldb,
|
559 |
+
const cuDoubleComplex* beta,
|
560 |
+
cuDoubleComplex* c,
|
561 |
+
const int* ldc);
|
562 |
+
|
563 |
+
/* SYR2K */
|
564 |
+
void ssyr2k_(const char* uplo,
|
565 |
+
const char* trans,
|
566 |
+
const int* n,
|
567 |
+
const int* k,
|
568 |
+
const float* alpha,
|
569 |
+
const float* a,
|
570 |
+
const int* lda,
|
571 |
+
const float* b,
|
572 |
+
const int* ldb,
|
573 |
+
const float* beta,
|
574 |
+
float* c,
|
575 |
+
const int* ldc);
|
576 |
+
|
577 |
+
void dsyr2k_(const char* uplo,
|
578 |
+
const char* trans,
|
579 |
+
const int* n,
|
580 |
+
const int* k,
|
581 |
+
const double* alpha,
|
582 |
+
const double* a,
|
583 |
+
const int* lda,
|
584 |
+
const double* b,
|
585 |
+
const int* ldb,
|
586 |
+
const double* beta,
|
587 |
+
double* c,
|
588 |
+
const int* ldc);
|
589 |
+
|
590 |
+
void csyr2k_(const char* uplo,
|
591 |
+
const char* trans,
|
592 |
+
const int* n,
|
593 |
+
const int* k,
|
594 |
+
const cuComplex* alpha,
|
595 |
+
const cuComplex* a,
|
596 |
+
const int* lda,
|
597 |
+
const cuComplex* b,
|
598 |
+
const int* ldb,
|
599 |
+
const cuComplex* beta,
|
600 |
+
cuComplex* c,
|
601 |
+
const int* ldc);
|
602 |
+
|
603 |
+
void zsyr2k_(const char* uplo,
|
604 |
+
const char* trans,
|
605 |
+
const int* n,
|
606 |
+
const int* k,
|
607 |
+
const cuDoubleComplex* alpha,
|
608 |
+
const cuDoubleComplex* a,
|
609 |
+
const int* lda,
|
610 |
+
const cuDoubleComplex* b,
|
611 |
+
const int* ldb,
|
612 |
+
const cuDoubleComplex* beta,
|
613 |
+
cuDoubleComplex* c,
|
614 |
+
const int* ldc);
|
615 |
+
|
616 |
+
/* SYR2K no_underscore*/
|
617 |
+
void ssyr2k(const char* uplo,
|
618 |
+
const char* trans,
|
619 |
+
const int* n,
|
620 |
+
const int* k,
|
621 |
+
const float* alpha,
|
622 |
+
const float* a,
|
623 |
+
const int* lda,
|
624 |
+
const float* b,
|
625 |
+
const int* ldb,
|
626 |
+
const float* beta,
|
627 |
+
float* c,
|
628 |
+
const int* ldc);
|
629 |
+
|
630 |
+
void dsyr2k(const char* uplo,
|
631 |
+
const char* trans,
|
632 |
+
const int* n,
|
633 |
+
const int* k,
|
634 |
+
const double* alpha,
|
635 |
+
const double* a,
|
636 |
+
const int* lda,
|
637 |
+
const double* b,
|
638 |
+
const int* ldb,
|
639 |
+
const double* beta,
|
640 |
+
double* c,
|
641 |
+
const int* ldc);
|
642 |
+
|
643 |
+
void csyr2k(const char* uplo,
|
644 |
+
const char* trans,
|
645 |
+
const int* n,
|
646 |
+
const int* k,
|
647 |
+
const cuComplex* alpha,
|
648 |
+
const cuComplex* a,
|
649 |
+
const int* lda,
|
650 |
+
const cuComplex* b,
|
651 |
+
const int* ldb,
|
652 |
+
const cuComplex* beta,
|
653 |
+
cuComplex* c,
|
654 |
+
const int* ldc);
|
655 |
+
|
656 |
+
void zsyr2k(const char* uplo,
|
657 |
+
const char* trans,
|
658 |
+
const int* n,
|
659 |
+
const int* k,
|
660 |
+
const cuDoubleComplex* alpha,
|
661 |
+
const cuDoubleComplex* a,
|
662 |
+
const int* lda,
|
663 |
+
const cuDoubleComplex* b,
|
664 |
+
const int* ldb,
|
665 |
+
const cuDoubleComplex* beta,
|
666 |
+
cuDoubleComplex* c,
|
667 |
+
const int* ldc);
|
668 |
+
|
669 |
+
/* HERK */
|
670 |
+
void cher2k_(const char* uplo,
|
671 |
+
const char* trans,
|
672 |
+
const int* n,
|
673 |
+
const int* k,
|
674 |
+
const cuComplex* alpha,
|
675 |
+
const cuComplex* a,
|
676 |
+
const int* lda,
|
677 |
+
const cuComplex* b,
|
678 |
+
const int* ldb,
|
679 |
+
const float* beta,
|
680 |
+
cuComplex* c,
|
681 |
+
const int* ldc);
|
682 |
+
|
683 |
+
void zher2k_(const char* uplo,
|
684 |
+
const char* trans,
|
685 |
+
const int* n,
|
686 |
+
const int* k,
|
687 |
+
const cuDoubleComplex* alpha,
|
688 |
+
const cuDoubleComplex* a,
|
689 |
+
const int* lda,
|
690 |
+
const cuDoubleComplex* b,
|
691 |
+
const int* ldb,
|
692 |
+
const double* beta,
|
693 |
+
cuDoubleComplex* c,
|
694 |
+
const int* ldc);
|
695 |
+
|
696 |
+
/* HER2K with no underscore */
|
697 |
+
void cher2k(const char* uplo,
|
698 |
+
const char* trans,
|
699 |
+
const int* n,
|
700 |
+
const int* k,
|
701 |
+
const cuComplex* alpha,
|
702 |
+
const cuComplex* a,
|
703 |
+
const int* lda,
|
704 |
+
const cuComplex* b,
|
705 |
+
const int* ldb,
|
706 |
+
const float* beta,
|
707 |
+
cuComplex* c,
|
708 |
+
const int* ldc);
|
709 |
+
|
710 |
+
void zher2k(const char* uplo,
|
711 |
+
const char* trans,
|
712 |
+
const int* n,
|
713 |
+
const int* k,
|
714 |
+
const cuDoubleComplex* alpha,
|
715 |
+
const cuDoubleComplex* a,
|
716 |
+
const int* lda,
|
717 |
+
const cuDoubleComplex* b,
|
718 |
+
const int* ldb,
|
719 |
+
const double* beta,
|
720 |
+
cuDoubleComplex* c,
|
721 |
+
const int* ldc);
|
722 |
+
|
723 |
+
/* TRMM */
|
724 |
+
void strmm_(const char* side,
|
725 |
+
const char* uplo,
|
726 |
+
const char* transa,
|
727 |
+
const char* diag,
|
728 |
+
const int* m,
|
729 |
+
const int* n,
|
730 |
+
const float* alpha,
|
731 |
+
const float* a,
|
732 |
+
const int* lda,
|
733 |
+
float* b,
|
734 |
+
const int* ldb);
|
735 |
+
|
736 |
+
void dtrmm_(const char* side,
|
737 |
+
const char* uplo,
|
738 |
+
const char* transa,
|
739 |
+
const char* diag,
|
740 |
+
const int* m,
|
741 |
+
const int* n,
|
742 |
+
const double* alpha,
|
743 |
+
const double* a,
|
744 |
+
const int* lda,
|
745 |
+
double* b,
|
746 |
+
const int* ldb);
|
747 |
+
|
748 |
+
void ctrmm_(const char* side,
|
749 |
+
const char* uplo,
|
750 |
+
const char* transa,
|
751 |
+
const char* diag,
|
752 |
+
const int* m,
|
753 |
+
const int* n,
|
754 |
+
const cuComplex* alpha,
|
755 |
+
const cuComplex* a,
|
756 |
+
const int* lda,
|
757 |
+
cuComplex* b,
|
758 |
+
const int* ldb);
|
759 |
+
|
760 |
+
void ztrmm_(const char* side,
|
761 |
+
const char* uplo,
|
762 |
+
const char* transa,
|
763 |
+
const char* diag,
|
764 |
+
const int* m,
|
765 |
+
const int* n,
|
766 |
+
const cuDoubleComplex* alpha,
|
767 |
+
const cuDoubleComplex* a,
|
768 |
+
const int* lda,
|
769 |
+
cuDoubleComplex* b,
|
770 |
+
const int* ldb);
|
771 |
+
|
772 |
+
void strmm(const char* side,
|
773 |
+
const char* uplo,
|
774 |
+
const char* transa,
|
775 |
+
const char* diag,
|
776 |
+
const int* m,
|
777 |
+
const int* n,
|
778 |
+
const float* alpha,
|
779 |
+
const float* a,
|
780 |
+
const int* lda,
|
781 |
+
float* b,
|
782 |
+
const int* ldb);
|
783 |
+
|
784 |
+
void dtrmm(const char* side,
|
785 |
+
const char* uplo,
|
786 |
+
const char* transa,
|
787 |
+
const char* diag,
|
788 |
+
const int* m,
|
789 |
+
const int* n,
|
790 |
+
const double* alpha,
|
791 |
+
const double* a,
|
792 |
+
const int* lda,
|
793 |
+
double* b,
|
794 |
+
const int* ldb);
|
795 |
+
|
796 |
+
void ctrmm(const char* side,
|
797 |
+
const char* uplo,
|
798 |
+
const char* transa,
|
799 |
+
const char* diag,
|
800 |
+
const int* m,
|
801 |
+
const int* n,
|
802 |
+
const cuComplex* alpha,
|
803 |
+
const cuComplex* a,
|
804 |
+
const int* lda,
|
805 |
+
cuComplex* b,
|
806 |
+
const int* ldb);
|
807 |
+
|
808 |
+
void ztrmm(const char* side,
|
809 |
+
const char* uplo,
|
810 |
+
const char* transa,
|
811 |
+
const char* diag,
|
812 |
+
const int* m,
|
813 |
+
const int* n,
|
814 |
+
const cuDoubleComplex* alpha,
|
815 |
+
const cuDoubleComplex* a,
|
816 |
+
const int* lda,
|
817 |
+
cuDoubleComplex* b,
|
818 |
+
const int* ldb);
|
819 |
+
|
820 |
+
#if defined(__cplusplus)
|
821 |
+
}
|
822 |
+
#endif /* __cplusplus */
|
823 |
+
|
824 |
+
#endif /* !defined(NVBLAS_H_) */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/lib/__init__.py
ADDED
File without changes
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/lib/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (182 Bytes). View file
|
|
env-llmeval/lib/python3.10/site-packages/nvidia/cublas/lib/libnvblas.so.12
ADDED
Binary file (737 kB). View file
|
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (184 Bytes). View file
|
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (192 Bytes). View file
|
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/builtin_types.h
ADDED
@@ -0,0 +1,64 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2014 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
/*******************************************************************************
|
51 |
+
* *
|
52 |
+
* *
|
53 |
+
* *
|
54 |
+
*******************************************************************************/
|
55 |
+
|
56 |
+
#include "device_types.h"
|
57 |
+
#if !defined(__CUDACC_RTC__)
|
58 |
+
#define EXCLUDE_FROM_RTC
|
59 |
+
#include "driver_types.h"
|
60 |
+
#undef EXCLUDE_FROM_RTC
|
61 |
+
#endif /* !__CUDACC_RTC__ */
|
62 |
+
#include "surface_types.h"
|
63 |
+
#include "texture_types.h"
|
64 |
+
#include "vector_types.h"
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/common_functions.h
ADDED
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2018 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
|
51 |
+
#if defined(_MSC_VER)
|
52 |
+
#pragma message("common_functions.h is an internal header file and must not be used directly. This file will be removed in a future CUDA release. Please use cuda_runtime_api.h or cuda_runtime.h instead.")
|
53 |
+
#else
|
54 |
+
#warning "common_functions.h is an internal header file and must not be used directly. This file will be removed in a future CUDA release. Please use cuda_runtime_api.h or cuda_runtime.h instead."
|
55 |
+
#endif
|
56 |
+
#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
57 |
+
#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_COMMON_FUNCTIONS_H_WRAPPER__
|
58 |
+
#endif
|
59 |
+
|
60 |
+
#include "crt/common_functions.h"
|
61 |
+
|
62 |
+
#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_COMMON_FUNCTIONS_H_WRAPPER__)
|
63 |
+
#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
64 |
+
#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_COMMON_FUNCTIONS_H_WRAPPER__
|
65 |
+
#endif
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/async.h
ADDED
@@ -0,0 +1,452 @@
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|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_ASYNC_H
|
50 |
+
#define _CG_ASYNC_H
|
51 |
+
|
52 |
+
#include "helpers.h"
|
53 |
+
#include "info.h"
|
54 |
+
|
55 |
+
#include <cuda_pipeline.h>
|
56 |
+
|
57 |
+
_CG_BEGIN_NAMESPACE
|
58 |
+
|
59 |
+
namespace details {
|
60 |
+
// Groups supported by memcpy_async
|
61 |
+
template <class TyGroup>
|
62 |
+
struct _async_copy_group_supported : public _CG_STL_NAMESPACE::false_type {};
|
63 |
+
|
64 |
+
template <unsigned int Sz, typename TyPar>
|
65 |
+
struct _async_copy_group_supported<cooperative_groups::thread_block_tile<Sz, TyPar>>
|
66 |
+
: public _CG_STL_NAMESPACE::true_type {};
|
67 |
+
template <>
|
68 |
+
struct _async_copy_group_supported<cooperative_groups::coalesced_group> : public _CG_STL_NAMESPACE::true_type {};
|
69 |
+
template <>
|
70 |
+
struct _async_copy_group_supported<cooperative_groups::thread_block> : public _CG_STL_NAMESPACE::true_type {};
|
71 |
+
|
72 |
+
template <class TyGroup>
|
73 |
+
using async_copy_group_supported = _async_copy_group_supported<details::remove_qual<TyGroup>>;
|
74 |
+
|
75 |
+
// Groups that require optimization
|
76 |
+
template <class TyGroup>
|
77 |
+
struct _async_copy_optimize_tile : public _CG_STL_NAMESPACE::false_type {};
|
78 |
+
|
79 |
+
template <typename TyPar>
|
80 |
+
struct _async_copy_optimize_tile<cooperative_groups::thread_block_tile<1, TyPar>>
|
81 |
+
: public _CG_STL_NAMESPACE::false_type {};
|
82 |
+
|
83 |
+
template <unsigned int Sz, typename TyPar>
|
84 |
+
struct _async_copy_optimize_tile<cooperative_groups::thread_block_tile<Sz, TyPar>>
|
85 |
+
: public _CG_STL_NAMESPACE::true_type {};
|
86 |
+
|
87 |
+
template <class TyGroup>
|
88 |
+
using async_copy_optimize_tile = _async_copy_optimize_tile<details::remove_qual<TyGroup>>;
|
89 |
+
|
90 |
+
// SFINAE helpers for tile optimizations
|
91 |
+
template <class TyGroup>
|
92 |
+
using enable_tile_optimization =
|
93 |
+
typename _CG_STL_NAMESPACE::enable_if<async_copy_optimize_tile<TyGroup>::value, void *>::type;
|
94 |
+
|
95 |
+
template <class TyGroup>
|
96 |
+
using disable_tile_optimization =
|
97 |
+
typename _CG_STL_NAMESPACE::enable_if<!async_copy_optimize_tile<TyGroup>::value, void *>::type;
|
98 |
+
|
99 |
+
// Segment for punning to aligned types
|
100 |
+
template <unsigned int N>
|
101 |
+
struct _Segment {
|
102 |
+
int _seg[N];
|
103 |
+
};
|
104 |
+
|
105 |
+
// Trivial layout guaranteed-aligned copy-async compatible segments
|
106 |
+
template <unsigned int N>
|
107 |
+
struct Segment;
|
108 |
+
template <>
|
109 |
+
struct __align__(4) Segment<1> : public _Segment<1>{};
|
110 |
+
template <>
|
111 |
+
struct __align__(8) Segment<2> : public _Segment<2>{};
|
112 |
+
template <>
|
113 |
+
struct __align__(16) Segment<4> : public _Segment<4>{};
|
114 |
+
|
115 |
+
// Interleaved element by element copies from source to dest
|
116 |
+
template <typename TyGroup, typename TyElem>
|
117 |
+
_CG_STATIC_QUALIFIER void inline_copy(TyGroup &group, TyElem *__restrict__ dst, const TyElem *__restrict__ src,
|
118 |
+
size_t count) {
|
119 |
+
const unsigned int rank = group.thread_rank();
|
120 |
+
const unsigned int stride = group.size();
|
121 |
+
|
122 |
+
for (size_t idx = rank; idx < count; idx += stride) {
|
123 |
+
dst[idx] = src[idx];
|
124 |
+
}
|
125 |
+
}
|
126 |
+
|
127 |
+
template <typename TyGroup, typename TyElem, enable_tile_optimization<TyGroup> = nullptr>
|
128 |
+
_CG_STATIC_QUALIFIER void accelerated_async_copy(TyGroup &group, TyElem *__restrict__ dst,
|
129 |
+
const TyElem *__restrict__ src, size_t count) {
|
130 |
+
static_assert(async_copy_group_supported<TyGroup>::value,
|
131 |
+
"Async copy is only supported for groups that represent private shared memory");
|
132 |
+
|
133 |
+
if (count == 0) {
|
134 |
+
return;
|
135 |
+
}
|
136 |
+
|
137 |
+
const bool dstIsNotShared = !__isShared(dst);
|
138 |
+
const bool srcIsNotGlobal = !__isGlobal(src);
|
139 |
+
|
140 |
+
if (dstIsNotShared || srcIsNotGlobal) {
|
141 |
+
inline_copy(group, dst, src, count);
|
142 |
+
return;
|
143 |
+
}
|
144 |
+
|
145 |
+
const unsigned int stride = group.size();
|
146 |
+
const unsigned int rank = group.thread_rank();
|
147 |
+
// Efficient copies require warps to operate on the same amount of work at each step.
|
148 |
+
// remainders are handled in a separate stage to prevent branching
|
149 |
+
const unsigned int subWarpMask = (stride - 1);
|
150 |
+
const unsigned int subwarpCopies = (subWarpMask & (unsigned int)count);
|
151 |
+
const unsigned int maxSubwarpRank = min(rank, subwarpCopies - 1);
|
152 |
+
|
153 |
+
const size_t warpCopies = (count & (~subWarpMask));
|
154 |
+
|
155 |
+
for (size_t idx = 0; idx < warpCopies; idx += stride) {
|
156 |
+
size_t _srcIdx = rank + idx;
|
157 |
+
size_t _dstIdx = rank + idx;
|
158 |
+
__pipeline_memcpy_async(dst + _dstIdx, src + _srcIdx, sizeof(TyElem));
|
159 |
+
}
|
160 |
+
|
161 |
+
if (subwarpCopies) {
|
162 |
+
size_t _srcIdx = warpCopies + maxSubwarpRank;
|
163 |
+
size_t _dstIdx = warpCopies + maxSubwarpRank;
|
164 |
+
__pipeline_memcpy_async(dst + _dstIdx, src + _srcIdx, sizeof(TyElem));
|
165 |
+
}
|
166 |
+
}
|
167 |
+
|
168 |
+
template <typename TyGroup, typename TyElem, disable_tile_optimization<TyGroup> = nullptr>
|
169 |
+
_CG_STATIC_QUALIFIER void accelerated_async_copy(TyGroup &group, TyElem *__restrict__ dst,
|
170 |
+
const TyElem *__restrict__ src, size_t count) {
|
171 |
+
static_assert(async_copy_group_supported<TyGroup>::value,
|
172 |
+
"Async copy is only supported for groups that represent private shared memory");
|
173 |
+
|
174 |
+
const bool dstIsNotShared = !__isShared(dst);
|
175 |
+
const bool srcIsNotGlobal = !__isGlobal(src);
|
176 |
+
|
177 |
+
if (dstIsNotShared || srcIsNotGlobal) {
|
178 |
+
inline_copy(group, dst, src, count);
|
179 |
+
return;
|
180 |
+
}
|
181 |
+
|
182 |
+
unsigned int stride = group.size();
|
183 |
+
unsigned int rank = group.thread_rank();
|
184 |
+
|
185 |
+
for (size_t idx = rank; idx < count; idx += stride) {
|
186 |
+
size_t _srcIdx = idx;
|
187 |
+
size_t _dstIdx = idx;
|
188 |
+
__pipeline_memcpy_async(dst + _dstIdx, src + _srcIdx, sizeof(TyElem));
|
189 |
+
}
|
190 |
+
}
|
191 |
+
|
192 |
+
// Determine best possible alignment given an input and initial conditions
|
193 |
+
// Attempts to generate as little code as possible, most likely should only be used with 1 and 2 byte alignments
|
194 |
+
template <unsigned int MinAlignment, unsigned int MaxAlignment>
|
195 |
+
_CG_STATIC_QUALIFIER uint32_t find_best_alignment(void *__restrict__ dst, const void *__restrict__ src) {
|
196 |
+
// Narrowing conversion intentional
|
197 |
+
uint32_t base1 = (uint32_t) reinterpret_cast<uintptr_t>(src);
|
198 |
+
uint32_t base2 = (uint32_t) reinterpret_cast<uintptr_t>(dst);
|
199 |
+
|
200 |
+
uint32_t diff = ((base1) ^ (base2)) & (MaxAlignment - 1);
|
201 |
+
|
202 |
+
// range [MaxAlignment, alignof(elem)], step: x >> 1
|
203 |
+
// over range of possible alignments, choose best available out of range
|
204 |
+
uint32_t out = MaxAlignment;
|
205 |
+
#pragma unroll
|
206 |
+
for (uint32_t alignment = (MaxAlignment >> 1); alignment >= MinAlignment; alignment >>= 1) {
|
207 |
+
if (alignment & diff)
|
208 |
+
out = alignment;
|
209 |
+
}
|
210 |
+
|
211 |
+
return out;
|
212 |
+
}
|
213 |
+
|
214 |
+
// Determine best possible alignment given an input and initial conditions
|
215 |
+
// Attempts to generate as little code as possible, most likely should only be used with 1 and 2 byte alignments
|
216 |
+
template <typename TyType, typename TyGroup>
|
217 |
+
_CG_STATIC_QUALIFIER void copy_like(const TyGroup &group, void *__restrict__ _dst, const void *__restrict__ _src,
|
218 |
+
size_t count) {
|
219 |
+
const char *src = reinterpret_cast<const char *>(_src);
|
220 |
+
char *dst = reinterpret_cast<char *>(_dst);
|
221 |
+
|
222 |
+
constexpr uint32_t targetAlignment = (uint32_t)alignof(TyType);
|
223 |
+
|
224 |
+
uint32_t base = (uint32_t) reinterpret_cast<uintptr_t>(src);
|
225 |
+
uint32_t alignOffset = ((~base) + 1) & (targetAlignment - 1);
|
226 |
+
|
227 |
+
inline_copy(group, dst, src, alignOffset);
|
228 |
+
count -= alignOffset;
|
229 |
+
src += alignOffset;
|
230 |
+
dst += alignOffset;
|
231 |
+
|
232 |
+
// Copy using the best available alignment, async_copy expects n-datums, not bytes
|
233 |
+
size_t asyncCount = count / sizeof(TyType);
|
234 |
+
accelerated_async_copy(group, reinterpret_cast<TyType *>(dst), reinterpret_cast<const TyType *>(src), asyncCount);
|
235 |
+
asyncCount *= sizeof(TyType);
|
236 |
+
|
237 |
+
count -= asyncCount;
|
238 |
+
src += asyncCount;
|
239 |
+
dst += asyncCount;
|
240 |
+
inline_copy(group, dst, src, count);
|
241 |
+
}
|
242 |
+
|
243 |
+
// We must determine alignment and manually align src/dst ourselves
|
244 |
+
template <size_t AlignHint>
|
245 |
+
struct _memcpy_async_align_dispatch {
|
246 |
+
template <typename TyGroup>
|
247 |
+
_CG_STATIC_QUALIFIER void copy(TyGroup &group, void *__restrict__ dst, const void *__restrict__ src, size_t count) {
|
248 |
+
uint32_t alignment = find_best_alignment<AlignHint, 16>(dst, src);
|
249 |
+
|
250 |
+
// Avoid copying the extra bytes if desired copy count is smaller
|
251 |
+
alignment = count < alignment ? AlignHint : alignment;
|
252 |
+
|
253 |
+
switch (alignment) {
|
254 |
+
default:
|
255 |
+
case 1:
|
256 |
+
inline_copy(group, reinterpret_cast<char *>(dst), reinterpret_cast<const char *>(src), count);
|
257 |
+
break;
|
258 |
+
case 2:
|
259 |
+
inline_copy(group, reinterpret_cast<short *>(dst), reinterpret_cast<const short *>(src), count >> 1);
|
260 |
+
break;
|
261 |
+
case 4:
|
262 |
+
copy_like<Segment<1>>(group, dst, src, count);
|
263 |
+
break;
|
264 |
+
case 8:
|
265 |
+
copy_like<Segment<2>>(group, dst, src, count);
|
266 |
+
break;
|
267 |
+
case 16:
|
268 |
+
copy_like<Segment<4>>(group, dst, src, count);
|
269 |
+
break;
|
270 |
+
}
|
271 |
+
}
|
272 |
+
};
|
273 |
+
|
274 |
+
// Specialization for 4 byte alignments
|
275 |
+
template <>
|
276 |
+
struct _memcpy_async_align_dispatch<4> {
|
277 |
+
template <typename TyGroup>
|
278 |
+
_CG_STATIC_QUALIFIER void copy(TyGroup &group, void *__restrict__ _dst, const void *__restrict__ _src,
|
279 |
+
size_t count) {
|
280 |
+
const Segment<1> *src = reinterpret_cast<const Segment<1> *>(_src);
|
281 |
+
Segment<1> *dst = reinterpret_cast<Segment<1> *>(_dst);
|
282 |
+
|
283 |
+
// Dispatch straight to aligned LDGSTS calls
|
284 |
+
accelerated_async_copy(group, dst, src, count / sizeof(*dst));
|
285 |
+
}
|
286 |
+
};
|
287 |
+
|
288 |
+
// Specialization for 8 byte alignments
|
289 |
+
template <>
|
290 |
+
struct _memcpy_async_align_dispatch<8> {
|
291 |
+
template <typename TyGroup>
|
292 |
+
_CG_STATIC_QUALIFIER void copy(TyGroup &group, void *__restrict__ _dst, const void *__restrict__ _src,
|
293 |
+
size_t count) {
|
294 |
+
const Segment<2> *src = reinterpret_cast<const Segment<2> *>(_src);
|
295 |
+
Segment<2> *dst = reinterpret_cast<Segment<2> *>(_dst);
|
296 |
+
|
297 |
+
// Dispatch straight to aligned LDGSTS calls
|
298 |
+
accelerated_async_copy(group, dst, src, count / sizeof(*dst));
|
299 |
+
}
|
300 |
+
};
|
301 |
+
|
302 |
+
// Alignments over 16 are truncated to 16 and bypass alignment
|
303 |
+
// This is the highest performing memcpy available
|
304 |
+
template <>
|
305 |
+
struct _memcpy_async_align_dispatch<16> {
|
306 |
+
template <typename TyGroup>
|
307 |
+
_CG_STATIC_QUALIFIER void copy(TyGroup &group, void *__restrict__ _dst, const void *__restrict__ _src,
|
308 |
+
size_t count) {
|
309 |
+
const Segment<4> *src = reinterpret_cast<const Segment<4> *>(_src);
|
310 |
+
Segment<4> *dst = reinterpret_cast<Segment<4> *>(_dst);
|
311 |
+
|
312 |
+
// Dispatch straight to aligned LDGSTS calls
|
313 |
+
accelerated_async_copy(group, dst, src, count / sizeof(*dst));
|
314 |
+
}
|
315 |
+
};
|
316 |
+
|
317 |
+
// byte-wide API
|
318 |
+
template <size_t Alignment, class TyGroup>
|
319 |
+
_CG_STATIC_QUALIFIER void _memcpy_async_dispatch_to_aligned_copy(const TyGroup &group, void *__restrict__ _dst,
|
320 |
+
const void *__restrict__ _src, size_t count) {
|
321 |
+
static_assert(!(Alignment & (Alignment - 1)), "Known static alignment dispatch must be a power of 2");
|
322 |
+
details::_memcpy_async_align_dispatch<Alignment>::copy(group, _dst, _src, count);
|
323 |
+
}
|
324 |
+
|
325 |
+
// Internal dispatch APIs
|
326 |
+
// These deduce the alignments and sizes necessary to invoke the underlying copy engine
|
327 |
+
template <typename Ty>
|
328 |
+
using is_void = _CG_STL_NAMESPACE::is_same<Ty, void>;
|
329 |
+
|
330 |
+
template <typename Ty>
|
331 |
+
using enable_if_not_void = typename _CG_STL_NAMESPACE::enable_if<!is_void<Ty>::value, void *>::type;
|
332 |
+
|
333 |
+
template <typename Ty>
|
334 |
+
using enable_if_void = typename _CG_STL_NAMESPACE::enable_if<is_void<Ty>::value, void *>::type;
|
335 |
+
|
336 |
+
template <typename Ty>
|
337 |
+
using enable_if_integral =
|
338 |
+
typename _CG_STL_NAMESPACE::enable_if<_CG_STL_NAMESPACE::is_integral<Ty>::value, void *>::type;
|
339 |
+
|
340 |
+
// byte-wide API using aligned_sized_t
|
341 |
+
template <class TyGroup, template <size_t> typename Alignment, size_t Hint>
|
342 |
+
_CG_STATIC_QUALIFIER void _memcpy_async_bytes(const TyGroup &group, void *__restrict__ _dst,
|
343 |
+
const void *__restrict__ _src, const Alignment<Hint> &count) {
|
344 |
+
constexpr size_t _align = (Hint > 16) ? 16 : Hint;
|
345 |
+
|
346 |
+
details::_memcpy_async_dispatch_to_aligned_copy<_align>(group, _dst, _src, (size_t)count);
|
347 |
+
}
|
348 |
+
|
349 |
+
// byte-wide API using type for aligment
|
350 |
+
template <class TyGroup, typename TyElem, typename TySize, size_t Hint = alignof(TyElem),
|
351 |
+
enable_if_not_void<TyElem> = nullptr, enable_if_integral<TySize> = nullptr>
|
352 |
+
_CG_STATIC_QUALIFIER void _memcpy_async_bytes(const TyGroup &group, TyElem *__restrict__ _dst,
|
353 |
+
const TyElem *__restrict__ _src, const TySize& count) {
|
354 |
+
constexpr size_t _align = (Hint > 16) ? 16 : Hint;
|
355 |
+
|
356 |
+
details::_memcpy_async_dispatch_to_aligned_copy<_align>(group, _dst, _src, count);
|
357 |
+
}
|
358 |
+
|
359 |
+
// byte-wide API with full alignment deduction required
|
360 |
+
template <class TyGroup, typename TyElem, typename TySize, enable_if_void<TyElem> = nullptr,
|
361 |
+
enable_if_integral<TySize> = nullptr>
|
362 |
+
_CG_STATIC_QUALIFIER void _memcpy_async_bytes(const TyGroup &group, TyElem *__restrict__ _dst,
|
363 |
+
const TyElem *__restrict__ _src, const TySize& count) {
|
364 |
+
details::_memcpy_async_dispatch_to_aligned_copy<1>(group, _dst, _src, count);
|
365 |
+
}
|
366 |
+
|
367 |
+
// 1d-datum API
|
368 |
+
template <class TyGroup, typename TyElem, size_t Hint = alignof(TyElem)>
|
369 |
+
_CG_STATIC_QUALIFIER void _memcpy_async_datum(const TyGroup &group, TyElem *__restrict__ dst, const size_t dstCount,
|
370 |
+
const TyElem *__restrict__ src, const size_t srcCount) {
|
371 |
+
constexpr unsigned int _align = Hint;
|
372 |
+
const size_t totalCount = min(dstCount, srcCount) * sizeof(TyElem);
|
373 |
+
|
374 |
+
details::_memcpy_async_dispatch_to_aligned_copy<_align>(group, dst, src, totalCount);
|
375 |
+
}
|
376 |
+
|
377 |
+
// 1d-datum API using aligned_size_t
|
378 |
+
template <class TyGroup, typename TyElem, template <size_t> typename Alignment, size_t Hint>
|
379 |
+
_CG_STATIC_QUALIFIER void _memcpy_async_datum(const TyGroup &group, TyElem *__restrict__ dst, const Alignment<Hint> &dstCount,
|
380 |
+
const TyElem *__restrict__ src, const Alignment<Hint> &srcCount) {
|
381 |
+
constexpr unsigned int _align = Hint;
|
382 |
+
const size_t totalCount = min((size_t)dstCount, (size_t)srcCount) * sizeof(TyElem);
|
383 |
+
|
384 |
+
details::_memcpy_async_dispatch_to_aligned_copy<_align>(group, dst, src, totalCount);
|
385 |
+
}
|
386 |
+
|
387 |
+
} // namespace details
|
388 |
+
|
389 |
+
/*
|
390 |
+
* Group submit batch of async-copy to cover contiguous 1D array
|
391 |
+
* and commit that batch to eventually wait for completion.
|
392 |
+
*/
|
393 |
+
template <class TyGroup, typename TyElem, typename TySizeT>
|
394 |
+
_CG_STATIC_QUALIFIER void memcpy_async(const TyGroup &group, TyElem *__restrict__ _dst, const TyElem *__restrict__ _src,
|
395 |
+
const TySizeT &count) {
|
396 |
+
details::_memcpy_async_bytes(group, _dst, _src, count);
|
397 |
+
__pipeline_commit();
|
398 |
+
}
|
399 |
+
|
400 |
+
/*
|
401 |
+
* Group submit batch of async-copy to cover contiguous 1D array
|
402 |
+
* and commit that batch to eventually wait for completion.
|
403 |
+
* Object counts are in datum sized chunks, not bytes.
|
404 |
+
*/
|
405 |
+
template <class TyGroup, class TyElem, typename DstLayout, typename SrcLayout>
|
406 |
+
_CG_STATIC_QUALIFIER void memcpy_async(const TyGroup &group, TyElem *__restrict__ dst, const DstLayout &dstLayout,
|
407 |
+
const TyElem *__restrict__ src, const SrcLayout &srcLayout) {
|
408 |
+
details::_memcpy_async_datum(group, dst, dstLayout, src, srcLayout);
|
409 |
+
__pipeline_commit();
|
410 |
+
}
|
411 |
+
|
412 |
+
/* Group wait for prior Nth stage of memcpy_async to complete. */
|
413 |
+
template <unsigned int Stage, class TyGroup>
|
414 |
+
_CG_STATIC_QUALIFIER void wait_prior(const TyGroup &group) {
|
415 |
+
__pipeline_wait_prior(Stage);
|
416 |
+
group.sync();
|
417 |
+
}
|
418 |
+
|
419 |
+
/* Group wait all previously submitted memcpy_async to complete. */
|
420 |
+
template <class TyGroup>
|
421 |
+
_CG_STATIC_QUALIFIER void wait(const TyGroup &group) {
|
422 |
+
__pipeline_wait_prior(0);
|
423 |
+
group.sync();
|
424 |
+
}
|
425 |
+
|
426 |
+
/***************** CG APIs including pipeline are deprecated *****************/
|
427 |
+
|
428 |
+
/* Group submit batch of async-copy to cover of contiguous 1D array
|
429 |
+
to a pipeline and commit the batch*/
|
430 |
+
template <class TyGroup, class TyElem>
|
431 |
+
_CG_DEPRECATED _CG_STATIC_QUALIFIER void memcpy_async(TyGroup &group, TyElem *dst, size_t dstCount, const TyElem *src, size_t srcCount,
|
432 |
+
nvcuda::experimental::pipeline &pipe) {
|
433 |
+
details::_memcpy_async_datum(group, dst, dstCount, src, srcCount);
|
434 |
+
pipe.commit();
|
435 |
+
}
|
436 |
+
|
437 |
+
/* Group wait for prior Nth stage of memcpy_async to complete. */
|
438 |
+
template <unsigned int Stage, class TyGroup>
|
439 |
+
_CG_DEPRECATED _CG_STATIC_QUALIFIER void wait_prior(TyGroup &group, nvcuda::experimental::pipeline &pipe) {
|
440 |
+
pipe.wait_prior<Stage>();
|
441 |
+
group.sync();
|
442 |
+
}
|
443 |
+
|
444 |
+
/* Group wait for stage-S of memcpy_async to complete. */
|
445 |
+
template <class TyGroup>
|
446 |
+
_CG_DEPRECATED _CG_STATIC_QUALIFIER void wait(TyGroup &group, nvcuda::experimental::pipeline &pipe, size_t stage) {
|
447 |
+
pipe.wait(stage);
|
448 |
+
group.sync();
|
449 |
+
}
|
450 |
+
_CG_END_NAMESPACE
|
451 |
+
|
452 |
+
#endif // _CG_ASYNC_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/coalesced_reduce.h
ADDED
@@ -0,0 +1,108 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_COALESCED_REDUCE_H_
|
50 |
+
#define _CG_COALESCED_REDUCE_H_
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
#include "helpers.h"
|
54 |
+
#include "cooperative_groups.h"
|
55 |
+
#include "partitioning.h"
|
56 |
+
#include "coalesced_scan.h"
|
57 |
+
|
58 |
+
_CG_BEGIN_NAMESPACE
|
59 |
+
|
60 |
+
namespace details {
|
61 |
+
|
62 |
+
template <typename TyVal, typename TyOp>
|
63 |
+
_CG_QUALIFIER auto coalesced_reduce_to_one(const coalesced_group& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
|
64 |
+
if (group.size() == 32) {
|
65 |
+
auto out = val;
|
66 |
+
for (int offset = group.size() >> 1; offset > 0; offset >>= 1) {
|
67 |
+
out = op(out, group.shfl_up(out, offset));
|
68 |
+
}
|
69 |
+
return out;
|
70 |
+
}
|
71 |
+
else {
|
72 |
+
auto scan_result =
|
73 |
+
inclusive_scan_non_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
74 |
+
return scan_result;
|
75 |
+
}
|
76 |
+
}
|
77 |
+
|
78 |
+
template <typename TyVal, typename TyOp>
|
79 |
+
_CG_QUALIFIER auto coalesced_reduce(const coalesced_group& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
|
80 |
+
auto out = coalesced_reduce_to_one(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
81 |
+
if (group.size() == 32) {
|
82 |
+
return group.shfl(out, 31);
|
83 |
+
}
|
84 |
+
else {
|
85 |
+
unsigned int group_mask = _coalesced_group_data_access::get_mask(group);
|
86 |
+
unsigned int last_thread_id = 31 - __clz(group_mask);
|
87 |
+
return details::tile::shuffle_dispatch<TyVal>::shfl(
|
88 |
+
_CG_STL_NAMESPACE::forward<TyVal>(out), group_mask, last_thread_id, 32);
|
89 |
+
}
|
90 |
+
}
|
91 |
+
|
92 |
+
template <typename TyVal, typename TyOp, unsigned int TySize, typename ParentT>
|
93 |
+
_CG_QUALIFIER auto coalesced_reduce(const __single_warp_thread_block_tile<TySize, ParentT>& group,
|
94 |
+
TyVal&& val,
|
95 |
+
TyOp&& op) -> decltype(op(val, val)) {
|
96 |
+
auto out = val;
|
97 |
+
for (int mask = TySize >> 1; mask > 0; mask >>= 1) {
|
98 |
+
out = op(out, group.shfl_xor(out, mask));
|
99 |
+
}
|
100 |
+
|
101 |
+
return out;
|
102 |
+
}
|
103 |
+
|
104 |
+
} // details
|
105 |
+
|
106 |
+
_CG_END_NAMESPACE
|
107 |
+
|
108 |
+
#endif // _CG_COALESCED_REDUCE_H_
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/coalesced_scan.h
ADDED
@@ -0,0 +1,174 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_COALESCED_SCAN_H_
|
50 |
+
#define _CG_COALESCED_SCAN_H_
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
#include "helpers.h"
|
54 |
+
#include "cooperative_groups.h"
|
55 |
+
#include "partitioning.h"
|
56 |
+
#include "functional.h"
|
57 |
+
|
58 |
+
_CG_BEGIN_NAMESPACE
|
59 |
+
|
60 |
+
namespace details {
|
61 |
+
|
62 |
+
template <typename TyGroup, typename TyVal, typename TyOp>
|
63 |
+
_CG_QUALIFIER auto inclusive_scan_contiguous(const TyGroup& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
|
64 |
+
auto out = val;
|
65 |
+
for (int mask = 1; mask < group.size(); mask <<= 1) {
|
66 |
+
auto tmp = group.shfl_up(out, mask);
|
67 |
+
if (mask <= group.thread_rank()) {
|
68 |
+
out = op(out, tmp);
|
69 |
+
}
|
70 |
+
}
|
71 |
+
|
72 |
+
return out;
|
73 |
+
}
|
74 |
+
|
75 |
+
template <typename TyGroup, typename TyVal, typename TyOp>
|
76 |
+
_CG_QUALIFIER auto inclusive_scan_non_contiguous(const TyGroup& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
|
77 |
+
const unsigned int groupSize = group.size();
|
78 |
+
auto out = val;
|
79 |
+
|
80 |
+
const unsigned int mask = details::_coalesced_group_data_access::get_mask(group);
|
81 |
+
unsigned int lanemask = details::lanemask32_lt() & mask;
|
82 |
+
unsigned int srcLane = details::laneid();
|
83 |
+
|
84 |
+
const unsigned int base = __ffs(mask)-1; /* lane with rank == 0 */
|
85 |
+
const unsigned int rank = __popc(lanemask);
|
86 |
+
|
87 |
+
for (unsigned int i = 1, j = 1; i < groupSize; i <<= 1) {
|
88 |
+
if (i <= rank) {
|
89 |
+
srcLane -= j;
|
90 |
+
j = i; /* maximum possible lane */
|
91 |
+
|
92 |
+
unsigned int begLane = base + rank - i; /* minimum possible lane */
|
93 |
+
|
94 |
+
/* Next source lane is in the range [ begLane .. srcLane ]
|
95 |
+
* If begLane < srcLane then do a binary search.
|
96 |
+
*/
|
97 |
+
while (begLane < srcLane) {
|
98 |
+
const unsigned int halfLane = (begLane + srcLane) >> 1;
|
99 |
+
const unsigned int halfMask = lanemask >> halfLane;
|
100 |
+
const unsigned int d = __popc(halfMask);
|
101 |
+
if (d < i) {
|
102 |
+
srcLane = halfLane - 1; /* halfLane too large */
|
103 |
+
}
|
104 |
+
else if ((i < d) || !(halfMask & 0x01)) {
|
105 |
+
begLane = halfLane + 1; /* halfLane too small */
|
106 |
+
}
|
107 |
+
else {
|
108 |
+
begLane = srcLane = halfLane; /* happen to hit */
|
109 |
+
}
|
110 |
+
}
|
111 |
+
}
|
112 |
+
|
113 |
+
auto tmp = details::tile::shuffle_dispatch<TyVal>::shfl(out, mask, srcLane, 32);
|
114 |
+
if (i <= rank) {
|
115 |
+
out = op(out, tmp);
|
116 |
+
}
|
117 |
+
}
|
118 |
+
return out;
|
119 |
+
}
|
120 |
+
|
121 |
+
template <unsigned int TySize, typename ParentT, typename TyVal, typename TyOp>
|
122 |
+
_CG_QUALIFIER auto coalesced_inclusive_scan(const __single_warp_thread_block_tile<TySize, ParentT>& group,
|
123 |
+
TyVal&& val,
|
124 |
+
TyOp&& op) -> decltype(op(val, val)) {
|
125 |
+
return inclusive_scan_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
126 |
+
}
|
127 |
+
|
128 |
+
template <typename TyVal, typename TyOp>
|
129 |
+
_CG_QUALIFIER auto coalesced_inclusive_scan(const coalesced_group& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
|
130 |
+
if (group.size() == 32) {
|
131 |
+
return inclusive_scan_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
132 |
+
}
|
133 |
+
else {
|
134 |
+
return inclusive_scan_non_contiguous(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
135 |
+
}
|
136 |
+
}
|
137 |
+
|
138 |
+
template <bool IntegralOptimized>
|
139 |
+
struct scan_choose_convertion;
|
140 |
+
|
141 |
+
template<>
|
142 |
+
struct scan_choose_convertion<true> {
|
143 |
+
template <typename TyGroup, typename TyRes, typename TyVal>
|
144 |
+
_CG_STATIC_QUALIFIER details::remove_qual<TyVal> convert_inclusive_to_exclusive(const TyGroup& group, TyRes& result, TyVal&& val) {
|
145 |
+
return result - val;
|
146 |
+
}
|
147 |
+
};
|
148 |
+
|
149 |
+
template<>
|
150 |
+
struct scan_choose_convertion<false> {
|
151 |
+
template <typename TyGroup, typename TyRes, typename TyVal>
|
152 |
+
_CG_STATIC_QUALIFIER details::remove_qual<TyVal> convert_inclusive_to_exclusive(const TyGroup& group, TyRes& result, TyVal&& val) {
|
153 |
+
auto ret = group.shfl_up(result, 1);
|
154 |
+
if (group.thread_rank() == 0) {
|
155 |
+
return {};
|
156 |
+
}
|
157 |
+
else {
|
158 |
+
return ret;
|
159 |
+
}
|
160 |
+
}
|
161 |
+
};
|
162 |
+
|
163 |
+
template <typename TyGroup, typename TyRes, typename TyVal, typename TyFn>
|
164 |
+
_CG_QUALIFIER auto convert_inclusive_to_exclusive(const TyGroup& group, TyRes& result, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
165 |
+
using conversion = scan_choose_convertion<_CG_STL_NAMESPACE::is_same<remove_qual<TyFn>, cooperative_groups::plus<remove_qual<TyVal>>>::value
|
166 |
+
&& _CG_STL_NAMESPACE::is_integral<remove_qual<TyVal>>::value>;
|
167 |
+
return conversion::convert_inclusive_to_exclusive(group, result, _CG_STL_NAMESPACE::forward<TyVal>(val));
|
168 |
+
}
|
169 |
+
|
170 |
+
} // details
|
171 |
+
|
172 |
+
_CG_END_NAMESPACE
|
173 |
+
|
174 |
+
#endif // _CG_COALESCED_SCAN_H_
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/driver_abi.h
ADDED
@@ -0,0 +1,99 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_DRIVER_API_H
|
50 |
+
#define _CG_DRIVER_API_H
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
|
54 |
+
_CG_BEGIN_NAMESPACE
|
55 |
+
|
56 |
+
namespace details {
|
57 |
+
template <unsigned int RegId>
|
58 |
+
_CG_QUALIFIER unsigned int load_env_reg() {
|
59 |
+
// Abort by default
|
60 |
+
_CG_ABORT();
|
61 |
+
return 0;
|
62 |
+
}
|
63 |
+
|
64 |
+
template <unsigned int HiReg, unsigned int LoReg>
|
65 |
+
_CG_QUALIFIER unsigned long long load_env_reg64() {
|
66 |
+
unsigned long long registerLo = load_env_reg<LoReg>();
|
67 |
+
unsigned long long registerHi = load_env_reg<HiReg>();
|
68 |
+
|
69 |
+
return (registerHi << 32) | registerLo;
|
70 |
+
}
|
71 |
+
|
72 |
+
// inline PTX for accessing registers requires an immediate for the special reg
|
73 |
+
# define LOAD_ENVREG(NUMBER) \
|
74 |
+
template <> _CG_QUALIFIER unsigned int load_env_reg<NUMBER>() { \
|
75 |
+
unsigned int r; \
|
76 |
+
asm ("mov.u32 %0, %%envreg" #NUMBER ";" : "=r"(r)); \
|
77 |
+
return r; \
|
78 |
+
}
|
79 |
+
|
80 |
+
// Instantiate loaders for registers used
|
81 |
+
LOAD_ENVREG(0);
|
82 |
+
LOAD_ENVREG(1);
|
83 |
+
LOAD_ENVREG(2);
|
84 |
+
# undef LOAD_ENVREG
|
85 |
+
|
86 |
+
struct grid_workspace {
|
87 |
+
unsigned int wsSize;
|
88 |
+
unsigned int barrier;
|
89 |
+
};
|
90 |
+
|
91 |
+
_CG_QUALIFIER grid_workspace* get_grid_workspace() {
|
92 |
+
unsigned long long gridWsAbiAddress = load_env_reg64<1, 2>();
|
93 |
+
// Interpret the address from envreg 1 and 2 as the driver's grid workspace
|
94 |
+
return (reinterpret_cast<grid_workspace*>(gridWsAbiAddress));
|
95 |
+
}
|
96 |
+
}
|
97 |
+
_CG_END_NAMESPACE
|
98 |
+
|
99 |
+
#endif // _CG_DRIVER_API_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/functional.h
ADDED
@@ -0,0 +1,212 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_FUNCTIONAL_H
|
50 |
+
#define _CG_FUNCTIONAL_H
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
#include "helpers.h"
|
54 |
+
|
55 |
+
#ifdef _CG_CPP11_FEATURES
|
56 |
+
#ifdef _CG_USE_CUDA_STL
|
57 |
+
# include <cuda/std/functional>
|
58 |
+
#endif
|
59 |
+
|
60 |
+
_CG_BEGIN_NAMESPACE
|
61 |
+
|
62 |
+
namespace details {
|
63 |
+
#ifdef _CG_USE_CUDA_STL
|
64 |
+
using cuda::std::plus;
|
65 |
+
using cuda::std::bit_and;
|
66 |
+
using cuda::std::bit_xor;
|
67 |
+
using cuda::std::bit_or;
|
68 |
+
#else
|
69 |
+
template <typename Ty> struct plus {__device__ __forceinline__ Ty operator()(Ty arg1, Ty arg2) const {return arg1 + arg2;}};
|
70 |
+
template <typename Ty> struct bit_and {__device__ __forceinline__ Ty operator()(Ty arg1, Ty arg2) const {return arg1 & arg2;}};
|
71 |
+
template <typename Ty> struct bit_xor {__device__ __forceinline__ Ty operator()(Ty arg1, Ty arg2) const {return arg1 ^ arg2;}};
|
72 |
+
template <typename Ty> struct bit_or {__device__ __forceinline__ Ty operator()(Ty arg1, Ty arg2) const {return arg1 | arg2;}};
|
73 |
+
#endif // _CG_USE_PLATFORM_STL
|
74 |
+
} // details
|
75 |
+
|
76 |
+
template <typename Ty>
|
77 |
+
struct plus : public details::plus<Ty> {};
|
78 |
+
|
79 |
+
template <typename Ty>
|
80 |
+
struct less {
|
81 |
+
__device__ __forceinline__ Ty operator()(Ty arg1, Ty arg2) const {
|
82 |
+
return (arg2 < arg1) ? arg2 : arg1;
|
83 |
+
}
|
84 |
+
};
|
85 |
+
|
86 |
+
template <typename Ty>
|
87 |
+
struct greater {
|
88 |
+
__device__ __forceinline__ Ty operator()(Ty arg1, Ty arg2) const {
|
89 |
+
return (arg1 < arg2) ? arg2 : arg1;
|
90 |
+
}
|
91 |
+
};
|
92 |
+
|
93 |
+
template <typename Ty>
|
94 |
+
struct bit_and : public details::bit_and<Ty> {};
|
95 |
+
|
96 |
+
template <typename Ty>
|
97 |
+
struct bit_xor : public details::bit_xor<Ty> {};
|
98 |
+
|
99 |
+
template <typename Ty>
|
100 |
+
struct bit_or : public details::bit_or<Ty> {};
|
101 |
+
|
102 |
+
#if defined(_CG_HAS_STL_ATOMICS)
|
103 |
+
namespace details {
|
104 |
+
template <class Ty>
|
105 |
+
using _atomic_is_type_supported = _CG_STL_NAMESPACE::integral_constant<bool,
|
106 |
+
_CG_STL_NAMESPACE::is_integral<Ty>::value && (sizeof(Ty) == 4 || sizeof(Ty) == 8)>;
|
107 |
+
|
108 |
+
template <typename TyOp> struct _atomic_op_supported : public _CG_STL_NAMESPACE::false_type {};
|
109 |
+
template <typename Ty> struct _atomic_op_supported<cooperative_groups::plus<Ty>> : public _atomic_is_type_supported<Ty> {};
|
110 |
+
template <typename Ty> struct _atomic_op_supported<cooperative_groups::less<Ty>> : public _atomic_is_type_supported<Ty> {};
|
111 |
+
template <typename Ty> struct _atomic_op_supported<cooperative_groups::greater<Ty>> : public _atomic_is_type_supported<Ty> {};
|
112 |
+
template <typename Ty> struct _atomic_op_supported<cooperative_groups::bit_and<Ty>> : public _atomic_is_type_supported<Ty> {};
|
113 |
+
template <typename Ty> struct _atomic_op_supported<cooperative_groups::bit_or<Ty>> : public _atomic_is_type_supported<Ty> {};
|
114 |
+
template <typename Ty> struct _atomic_op_supported<cooperative_groups::bit_xor<Ty>> : public _atomic_is_type_supported<Ty> {};
|
115 |
+
|
116 |
+
template<typename TyAtomic, typename TyVal, typename TyOp>
|
117 |
+
_CG_QUALIFIER remove_qual<TyVal> atomic_cas_fallback(TyAtomic&& atomic, TyVal&& val, TyOp&& op) {
|
118 |
+
auto old = atomic.load(cuda::std::memory_order_relaxed);
|
119 |
+
while(!atomic.compare_exchange_weak(old, op(old, val), cuda::std::memory_order_relaxed));
|
120 |
+
return old;
|
121 |
+
}
|
122 |
+
|
123 |
+
template<typename TyOp>
|
124 |
+
struct op_picker;
|
125 |
+
|
126 |
+
template<typename TyVal>
|
127 |
+
struct op_picker<cooperative_groups::plus<TyVal>> {
|
128 |
+
template<typename TyAtomic>
|
129 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val) {
|
130 |
+
return atomic.fetch_add(val, cuda::std::memory_order_relaxed);
|
131 |
+
}
|
132 |
+
};
|
133 |
+
|
134 |
+
template<typename TyVal>
|
135 |
+
struct op_picker<cooperative_groups::less<TyVal>> {
|
136 |
+
template<typename TyAtomic>
|
137 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val) {
|
138 |
+
return atomic.fetch_min(val, cuda::std::memory_order_relaxed);
|
139 |
+
}
|
140 |
+
};
|
141 |
+
|
142 |
+
template<typename TyVal>
|
143 |
+
struct op_picker<cooperative_groups::greater<TyVal>> {
|
144 |
+
template<typename TyAtomic>
|
145 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val) {
|
146 |
+
return atomic.fetch_max(val, cuda::std::memory_order_relaxed);
|
147 |
+
}
|
148 |
+
};
|
149 |
+
|
150 |
+
template<typename TyVal>
|
151 |
+
struct op_picker<cooperative_groups::bit_and<TyVal>> {
|
152 |
+
template<typename TyAtomic>
|
153 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val) {
|
154 |
+
return atomic.fetch_and(val, cuda::std::memory_order_relaxed);
|
155 |
+
}
|
156 |
+
};
|
157 |
+
|
158 |
+
template<typename TyVal>
|
159 |
+
struct op_picker<cooperative_groups::bit_xor<TyVal>> {
|
160 |
+
template<typename TyAtomic>
|
161 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val) {
|
162 |
+
return atomic.fetch_xor(val, cuda::std::memory_order_relaxed);
|
163 |
+
}
|
164 |
+
};
|
165 |
+
|
166 |
+
template<typename TyVal>
|
167 |
+
struct op_picker<cooperative_groups::bit_or<TyVal>> {
|
168 |
+
template<typename TyAtomic>
|
169 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val) {
|
170 |
+
return atomic.fetch_or(val, cuda::std::memory_order_relaxed);
|
171 |
+
}
|
172 |
+
};
|
173 |
+
|
174 |
+
template<bool atomic_supported>
|
175 |
+
struct atomic_update_dispatch {};
|
176 |
+
|
177 |
+
template<>
|
178 |
+
struct atomic_update_dispatch<false> {
|
179 |
+
template<typename TyAtomic, typename TyVal, typename TyOp>
|
180 |
+
_CG_STATIC_QUALIFIER remove_qual<TyVal> atomic_update(TyAtomic& atomic, TyVal&& val, TyOp&& op) {
|
181 |
+
return atomic_cas_fallback(atomic, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
182 |
+
}
|
183 |
+
};
|
184 |
+
|
185 |
+
template<>
|
186 |
+
struct atomic_update_dispatch<true> {
|
187 |
+
template<typename TyAtomic, typename TyVal, typename TyOp>
|
188 |
+
_CG_STATIC_QUALIFIER TyVal atomic_update(TyAtomic& atomic, TyVal val, TyOp&& op) {
|
189 |
+
using dispatch = op_picker<details::remove_qual<TyOp>>;
|
190 |
+
|
191 |
+
return dispatch::atomic_update(atomic, val);
|
192 |
+
}
|
193 |
+
};
|
194 |
+
|
195 |
+
template<typename TyAtomic, typename TyVal, typename TyOp>
|
196 |
+
_CG_QUALIFIER remove_qual<TyVal> atomic_update(TyAtomic& atomic, TyVal&& val, TyOp&& op) {
|
197 |
+
using dispatch = atomic_update_dispatch<_atomic_op_supported<details::remove_qual<TyOp>>::value>;
|
198 |
+
|
199 |
+
return dispatch::atomic_update(atomic, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
200 |
+
}
|
201 |
+
|
202 |
+
template<typename TyAtomic, typename TyVal>
|
203 |
+
_CG_QUALIFIER void atomic_store(TyAtomic& atomic, TyVal&& val) {
|
204 |
+
atomic.store(val, cuda::std::memory_order_relaxed);
|
205 |
+
}
|
206 |
+
}
|
207 |
+
#endif
|
208 |
+
|
209 |
+
_CG_END_NAMESPACE
|
210 |
+
|
211 |
+
#endif
|
212 |
+
#endif //_CG_FUNCTIONAL_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/helpers.h
ADDED
@@ -0,0 +1,634 @@
|
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|
1 |
+
/* Copyright 1993-2021 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _COOPERATIVE_GROUPS_HELPERS_H_
|
50 |
+
# define _COOPERATIVE_GROUPS_HELPERS_H_
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
#include "sync.h"
|
54 |
+
|
55 |
+
_CG_BEGIN_NAMESPACE
|
56 |
+
|
57 |
+
namespace details {
|
58 |
+
#ifdef _CG_CPP11_FEATURES
|
59 |
+
template <typename Ty> struct _is_float_or_half : public _CG_STL_NAMESPACE::is_floating_point<Ty> {};
|
60 |
+
# ifdef _CG_HAS_FP16_COLLECTIVE
|
61 |
+
template <> struct _is_float_or_half<__half> : public _CG_STL_NAMESPACE::true_type {};
|
62 |
+
template <> struct _is_float_or_half<__half2> : public _CG_STL_NAMESPACE::true_type {};
|
63 |
+
# endif
|
64 |
+
template <typename Ty>
|
65 |
+
using is_float_or_half = _is_float_or_half<typename _CG_STL_NAMESPACE::remove_cv<Ty>::type>;
|
66 |
+
|
67 |
+
// Non-STL utility templates
|
68 |
+
template <typename Ty>
|
69 |
+
using remove_qual = typename _CG_STL_NAMESPACE::remove_cv<typename _CG_STL_NAMESPACE::remove_reference<Ty>::type>::type;
|
70 |
+
|
71 |
+
template <typename TyLhs, typename TyRhs>
|
72 |
+
using is_op_type_same = _CG_STL_NAMESPACE::is_same<remove_qual<TyLhs>, remove_qual<TyRhs>
|
73 |
+
>;
|
74 |
+
#endif
|
75 |
+
|
76 |
+
template <typename TyTrunc>
|
77 |
+
_CG_STATIC_QUALIFIER TyTrunc vec3_to_linear(dim3 index, dim3 nIndex) {
|
78 |
+
return ((TyTrunc)index.z * nIndex.y * nIndex.x) +
|
79 |
+
((TyTrunc)index.y * nIndex.x) +
|
80 |
+
(TyTrunc)index.x;
|
81 |
+
}
|
82 |
+
|
83 |
+
namespace cta {
|
84 |
+
|
85 |
+
_CG_STATIC_QUALIFIER void sync()
|
86 |
+
{
|
87 |
+
__barrier_sync(0);
|
88 |
+
}
|
89 |
+
|
90 |
+
_CG_STATIC_QUALIFIER unsigned int num_threads()
|
91 |
+
{
|
92 |
+
return static_cast<unsigned int>(blockDim.x * blockDim.y * blockDim.z);
|
93 |
+
}
|
94 |
+
|
95 |
+
_CG_STATIC_QUALIFIER unsigned int thread_rank()
|
96 |
+
{
|
97 |
+
return vec3_to_linear<unsigned int>(threadIdx, blockDim);
|
98 |
+
}
|
99 |
+
|
100 |
+
_CG_STATIC_QUALIFIER dim3 group_index()
|
101 |
+
{
|
102 |
+
return dim3(blockIdx.x, blockIdx.y, blockIdx.z);
|
103 |
+
}
|
104 |
+
|
105 |
+
_CG_STATIC_QUALIFIER dim3 thread_index()
|
106 |
+
{
|
107 |
+
return dim3(threadIdx.x, threadIdx.y, threadIdx.z);
|
108 |
+
}
|
109 |
+
|
110 |
+
_CG_STATIC_QUALIFIER dim3 dim_threads()
|
111 |
+
{
|
112 |
+
return dim3(blockDim.x, blockDim.y, blockDim.z);
|
113 |
+
}
|
114 |
+
|
115 |
+
// Legacy aliases
|
116 |
+
_CG_STATIC_QUALIFIER unsigned int size()
|
117 |
+
{
|
118 |
+
return num_threads();
|
119 |
+
}
|
120 |
+
|
121 |
+
_CG_STATIC_QUALIFIER dim3 block_dim()
|
122 |
+
{
|
123 |
+
return dim_threads();
|
124 |
+
}
|
125 |
+
|
126 |
+
};
|
127 |
+
|
128 |
+
class _coalesced_group_data_access {
|
129 |
+
public:
|
130 |
+
// Retrieve mask of coalesced groups and tiles
|
131 |
+
template <typename TyGroup>
|
132 |
+
_CG_STATIC_QUALIFIER unsigned int get_mask(const TyGroup &group) {
|
133 |
+
return group.get_mask();
|
134 |
+
}
|
135 |
+
|
136 |
+
template <typename TyGroup>
|
137 |
+
_CG_STATIC_QUALIFIER TyGroup construct_from_mask(unsigned int mask) {
|
138 |
+
return TyGroup(mask);
|
139 |
+
}
|
140 |
+
|
141 |
+
template <typename TyGroup>
|
142 |
+
_CG_STATIC_QUALIFIER void modify_meta_group(TyGroup &group, unsigned int mgRank, unsigned int mgSize) {
|
143 |
+
group._data.coalesced.metaGroupRank = mgRank;
|
144 |
+
group._data.coalesced.metaGroupSize = mgSize;
|
145 |
+
}
|
146 |
+
};
|
147 |
+
|
148 |
+
namespace tile {
|
149 |
+
template <unsigned int TileCount, unsigned int TileMask, unsigned int LaneMask, unsigned int ShiftCount>
|
150 |
+
struct _tile_helpers{
|
151 |
+
_CG_STATIC_CONST_DECL unsigned int tileCount = TileCount;
|
152 |
+
_CG_STATIC_CONST_DECL unsigned int tileMask = TileMask;
|
153 |
+
_CG_STATIC_CONST_DECL unsigned int laneMask = LaneMask;
|
154 |
+
_CG_STATIC_CONST_DECL unsigned int shiftCount = ShiftCount;
|
155 |
+
};
|
156 |
+
|
157 |
+
template <unsigned int> struct tile_helpers;
|
158 |
+
template <> struct tile_helpers<32> : public _tile_helpers<1, 0xFFFFFFFF, 0x1F, 5> {};
|
159 |
+
template <> struct tile_helpers<16> : public _tile_helpers<2, 0x0000FFFF, 0x0F, 4> {};
|
160 |
+
template <> struct tile_helpers<8> : public _tile_helpers<4, 0x000000FF, 0x07, 3> {};
|
161 |
+
template <> struct tile_helpers<4> : public _tile_helpers<8, 0x0000000F, 0x03, 2> {};
|
162 |
+
template <> struct tile_helpers<2> : public _tile_helpers<16, 0x00000003, 0x01, 1> {};
|
163 |
+
template <> struct tile_helpers<1> : public _tile_helpers<32, 0x00000001, 0x00, 0> {};
|
164 |
+
|
165 |
+
#ifdef _CG_CPP11_FEATURES
|
166 |
+
namespace shfl {
|
167 |
+
/***********************************************************************************
|
168 |
+
* Recursively Sliced Shuffle
|
169 |
+
* Purpose:
|
170 |
+
* Slices an input type a number of times into integral types so that shuffles
|
171 |
+
* are well defined
|
172 |
+
* Expectations:
|
173 |
+
* This object *should not* be used from a reinterpret_cast pointer unless
|
174 |
+
* some alignment guarantees can be met. Use a memcpy to guarantee that loads
|
175 |
+
* from the integral types stored within are aligned and correct.
|
176 |
+
**********************************************************************************/
|
177 |
+
template <unsigned int count, bool intSized = (count <= sizeof(int))>
|
178 |
+
struct recursive_sliced_shuffle_helper;
|
179 |
+
|
180 |
+
template <unsigned int count>
|
181 |
+
struct recursive_sliced_shuffle_helper<count, true> {
|
182 |
+
int val;
|
183 |
+
|
184 |
+
template <typename TyFn>
|
185 |
+
_CG_QUALIFIER void invoke_shuffle(const TyFn &shfl) {
|
186 |
+
val = shfl(val);
|
187 |
+
}
|
188 |
+
};
|
189 |
+
|
190 |
+
template <unsigned int count>
|
191 |
+
struct recursive_sliced_shuffle_helper<count, false> {
|
192 |
+
int val;
|
193 |
+
recursive_sliced_shuffle_helper<count - sizeof(int)> next;
|
194 |
+
|
195 |
+
template <typename TyFn>
|
196 |
+
_CG_QUALIFIER void invoke_shuffle(const TyFn &shfl) {
|
197 |
+
val = shfl(val);
|
198 |
+
next.invoke_shuffle(shfl);
|
199 |
+
}
|
200 |
+
};
|
201 |
+
}
|
202 |
+
|
203 |
+
struct _memory_shuffle {
|
204 |
+
template <typename TyElem, typename TyShflFn>
|
205 |
+
_CG_STATIC_QUALIFIER TyElem _shfl_internal(TyElem elem, const TyShflFn& fn) {
|
206 |
+
static_assert(sizeof(TyElem) <= 32, "Cooperative groups collectives are limited to types smaller than 32B");
|
207 |
+
return TyElem{};
|
208 |
+
}
|
209 |
+
|
210 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
211 |
+
_CG_STATIC_QUALIFIER TyRet shfl(TyElem&& elem, unsigned int gMask, unsigned int srcRank, unsigned int threads) {
|
212 |
+
auto shfl = [=](int val) -> int {
|
213 |
+
return 0;
|
214 |
+
};
|
215 |
+
|
216 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
217 |
+
}
|
218 |
+
|
219 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
220 |
+
_CG_STATIC_QUALIFIER TyRet shfl_down(TyElem&& elem, unsigned int gMask, unsigned int delta, unsigned int threads) {
|
221 |
+
auto shfl = [=](int val) -> int {
|
222 |
+
return 0;
|
223 |
+
};
|
224 |
+
|
225 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
226 |
+
}
|
227 |
+
|
228 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
229 |
+
_CG_STATIC_QUALIFIER TyRet shfl_up(TyElem&& elem, unsigned int gMask, unsigned int delta, unsigned int threads) {
|
230 |
+
auto shfl = [=](int val) -> int {
|
231 |
+
return 0;
|
232 |
+
};
|
233 |
+
|
234 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
235 |
+
}
|
236 |
+
|
237 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
238 |
+
_CG_STATIC_QUALIFIER TyRet shfl_xor(TyElem&& elem, unsigned int gMask, unsigned int lMask, unsigned int threads) {
|
239 |
+
auto shfl = [=](int val) -> int {
|
240 |
+
return 0;
|
241 |
+
};
|
242 |
+
|
243 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
244 |
+
}
|
245 |
+
};
|
246 |
+
|
247 |
+
/***********************************************************************************
|
248 |
+
* Intrinsic Device Function Shuffle
|
249 |
+
* Purpose:
|
250 |
+
* Uses a shuffle helper that has characteristics best suited for moving
|
251 |
+
* elements between threads
|
252 |
+
* Expectations:
|
253 |
+
* Object given will be forced into an l-value type so that it can be used
|
254 |
+
* with a helper structure that reinterprets the data into intrinsic compatible
|
255 |
+
* types
|
256 |
+
* Notes:
|
257 |
+
* !! TyRet is required so that objects are returned by value and not as
|
258 |
+
* dangling references depending on the value category of the passed object
|
259 |
+
**********************************************************************************/
|
260 |
+
struct _intrinsic_compat_shuffle {
|
261 |
+
template <unsigned int count>
|
262 |
+
using shfl_helper = shfl::recursive_sliced_shuffle_helper<count>;
|
263 |
+
|
264 |
+
template <typename TyElem, typename TyShflFn>
|
265 |
+
_CG_STATIC_QUALIFIER TyElem _shfl_internal(TyElem elem, const TyShflFn& fn) {
|
266 |
+
static_assert(__is_trivially_copyable(TyElem), "Type is not compatible with device shuffle");
|
267 |
+
shfl_helper<sizeof(TyElem)> helper;
|
268 |
+
memcpy(&helper, &elem, sizeof(TyElem));
|
269 |
+
helper.invoke_shuffle(fn);
|
270 |
+
memcpy(&elem, &helper, sizeof(TyElem));
|
271 |
+
return elem;
|
272 |
+
}
|
273 |
+
|
274 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
275 |
+
_CG_STATIC_QUALIFIER TyRet shfl(TyElem&& elem, unsigned int gMask, unsigned int srcRank, unsigned int threads) {
|
276 |
+
auto shfl = [=](int val) -> int {
|
277 |
+
return __shfl_sync(gMask, val, srcRank, threads);
|
278 |
+
};
|
279 |
+
|
280 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
281 |
+
}
|
282 |
+
|
283 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
284 |
+
_CG_STATIC_QUALIFIER TyRet shfl_down(TyElem&& elem, unsigned int gMask, unsigned int delta, unsigned int threads) {
|
285 |
+
auto shfl = [=](int val) -> int {
|
286 |
+
return __shfl_down_sync(gMask, val, delta, threads);
|
287 |
+
};
|
288 |
+
|
289 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
290 |
+
}
|
291 |
+
|
292 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
293 |
+
_CG_STATIC_QUALIFIER TyRet shfl_up(TyElem&& elem, unsigned int gMask, unsigned int delta, unsigned int threads) {
|
294 |
+
auto shfl = [=](int val) -> int {
|
295 |
+
return __shfl_up_sync(gMask, val, delta, threads);
|
296 |
+
};
|
297 |
+
|
298 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
299 |
+
}
|
300 |
+
|
301 |
+
template <typename TyElem, typename TyRet = remove_qual<TyElem>>
|
302 |
+
_CG_STATIC_QUALIFIER TyRet shfl_xor(TyElem&& elem, unsigned int gMask, unsigned int lMask, unsigned int threads) {
|
303 |
+
auto shfl = [=](int val) -> int {
|
304 |
+
return __shfl_xor_sync(gMask, val, lMask, threads);
|
305 |
+
};
|
306 |
+
|
307 |
+
return _shfl_internal<TyRet>(_CG_STL_NAMESPACE::forward<TyElem>(elem), shfl);
|
308 |
+
}
|
309 |
+
};
|
310 |
+
|
311 |
+
struct _native_shuffle {
|
312 |
+
template <typename TyElem>
|
313 |
+
_CG_STATIC_QUALIFIER TyElem shfl(
|
314 |
+
TyElem elem, unsigned int gMask, unsigned int srcRank, unsigned int threads) {
|
315 |
+
return static_cast<TyElem>(__shfl_sync(gMask, elem, srcRank, threads));
|
316 |
+
}
|
317 |
+
|
318 |
+
template <typename TyElem>
|
319 |
+
_CG_STATIC_QUALIFIER TyElem shfl_down(
|
320 |
+
TyElem elem, unsigned int gMask, unsigned int delta, unsigned int threads) {
|
321 |
+
return static_cast<TyElem>(__shfl_down_sync(gMask, elem, delta, threads));
|
322 |
+
}
|
323 |
+
|
324 |
+
template <typename TyElem>
|
325 |
+
_CG_STATIC_QUALIFIER TyElem shfl_up(
|
326 |
+
TyElem elem, unsigned int gMask, unsigned int delta, unsigned int threads) {
|
327 |
+
return static_cast<TyElem>(__shfl_up_sync(gMask, elem, delta, threads));
|
328 |
+
}
|
329 |
+
|
330 |
+
template <typename TyElem>
|
331 |
+
_CG_STATIC_QUALIFIER TyElem shfl_xor(
|
332 |
+
TyElem elem, unsigned int gMask, unsigned int lMask, unsigned int threads) {
|
333 |
+
return static_cast<TyElem>(__shfl_xor_sync(gMask, elem, lMask, threads));
|
334 |
+
}
|
335 |
+
};
|
336 |
+
|
337 |
+
// Almost all arithmetic types are supported by native shuffle
|
338 |
+
// Vector types are the exception
|
339 |
+
template <typename TyElem>
|
340 |
+
using use_native_shuffle = _CG_STL_NAMESPACE::integral_constant<
|
341 |
+
bool,
|
342 |
+
_CG_STL_NAMESPACE::is_integral<
|
343 |
+
remove_qual<TyElem>>::value ||
|
344 |
+
details::is_float_or_half<
|
345 |
+
remove_qual<TyElem>>::value
|
346 |
+
>;
|
347 |
+
|
348 |
+
constexpr unsigned long long _MemoryShuffleCutoff = 32;
|
349 |
+
|
350 |
+
template <typename TyElem,
|
351 |
+
bool IsNative = use_native_shuffle<TyElem>::value,
|
352 |
+
bool InMem = (sizeof(TyElem) > _MemoryShuffleCutoff)>
|
353 |
+
struct shuffle_dispatch;
|
354 |
+
|
355 |
+
template <typename TyElem>
|
356 |
+
struct shuffle_dispatch<TyElem, true, false> : public _native_shuffle {};
|
357 |
+
|
358 |
+
template <typename TyElem>
|
359 |
+
struct shuffle_dispatch<TyElem, false, false> : public _intrinsic_compat_shuffle {};
|
360 |
+
|
361 |
+
template <typename TyElem>
|
362 |
+
struct shuffle_dispatch<TyElem, false, true> : public _memory_shuffle {};
|
363 |
+
|
364 |
+
#endif //_CG_CPP11_FEATURES
|
365 |
+
};
|
366 |
+
|
367 |
+
namespace multi_grid {
|
368 |
+
struct multi_grid_functions;
|
369 |
+
};
|
370 |
+
|
371 |
+
namespace grid {
|
372 |
+
_CG_STATIC_QUALIFIER void sync(unsigned int *bar) {
|
373 |
+
unsigned int expected = gridDim.x * gridDim.y * gridDim.z;
|
374 |
+
|
375 |
+
details::sync_grids(expected, bar);
|
376 |
+
}
|
377 |
+
|
378 |
+
_CG_STATIC_QUALIFIER unsigned long long num_blocks()
|
379 |
+
{
|
380 |
+
// grid.y * grid.z -> [max(65535) * max(65535)] fits within 4b, promote after multiplication
|
381 |
+
// grid.x * (grid.y * grid.z) -> [max(2^31-1) * max(65535 * 65535)] exceeds 4b, promote before multiplication
|
382 |
+
return (unsigned long long)gridDim.x * (gridDim.y * gridDim.z);
|
383 |
+
}
|
384 |
+
|
385 |
+
_CG_STATIC_QUALIFIER unsigned long long num_threads()
|
386 |
+
{
|
387 |
+
return num_blocks() * cta::num_threads();
|
388 |
+
}
|
389 |
+
|
390 |
+
_CG_STATIC_QUALIFIER unsigned long long block_rank()
|
391 |
+
{
|
392 |
+
return vec3_to_linear<unsigned long long>(blockIdx, gridDim);
|
393 |
+
}
|
394 |
+
|
395 |
+
_CG_STATIC_QUALIFIER unsigned long long thread_rank()
|
396 |
+
{
|
397 |
+
return block_rank() * cta::num_threads() + cta::thread_rank();
|
398 |
+
}
|
399 |
+
|
400 |
+
_CG_STATIC_QUALIFIER dim3 dim_blocks()
|
401 |
+
{
|
402 |
+
return dim3(gridDim.x, gridDim.y, gridDim.z);
|
403 |
+
}
|
404 |
+
|
405 |
+
_CG_STATIC_QUALIFIER dim3 block_index()
|
406 |
+
{
|
407 |
+
return dim3(blockIdx.x, blockIdx.y, blockIdx.z);
|
408 |
+
}
|
409 |
+
|
410 |
+
#if defined(_CG_HAS_CLUSTER_GROUP)
|
411 |
+
_CG_STATIC_QUALIFIER dim3 dim_clusters() {
|
412 |
+
return __clusterGridDimInClusters();
|
413 |
+
}
|
414 |
+
|
415 |
+
_CG_STATIC_QUALIFIER unsigned long long num_clusters() {
|
416 |
+
const dim3 dimClusters = dim_clusters();
|
417 |
+
return dimClusters.x * dimClusters.y * dimClusters.z;
|
418 |
+
}
|
419 |
+
|
420 |
+
_CG_STATIC_QUALIFIER dim3 cluster_index() {
|
421 |
+
return __clusterIdx();
|
422 |
+
}
|
423 |
+
|
424 |
+
_CG_STATIC_QUALIFIER unsigned long long cluster_rank() {
|
425 |
+
return vec3_to_linear<unsigned long long>(cluster_index(), dim_clusters());
|
426 |
+
}
|
427 |
+
#endif
|
428 |
+
|
429 |
+
// Legacy aliases
|
430 |
+
_CG_STATIC_QUALIFIER unsigned long long size()
|
431 |
+
{
|
432 |
+
return num_threads();
|
433 |
+
}
|
434 |
+
|
435 |
+
_CG_STATIC_QUALIFIER dim3 grid_dim()
|
436 |
+
{
|
437 |
+
return dim_blocks();
|
438 |
+
}
|
439 |
+
};
|
440 |
+
|
441 |
+
|
442 |
+
#if defined(_CG_HAS_MULTI_GRID_GROUP)
|
443 |
+
|
444 |
+
namespace multi_grid {
|
445 |
+
_CG_STATIC_QUALIFIER unsigned long long get_intrinsic_handle()
|
446 |
+
{
|
447 |
+
return (cudaCGGetIntrinsicHandle(cudaCGScopeMultiGrid));
|
448 |
+
}
|
449 |
+
|
450 |
+
_CG_STATIC_QUALIFIER void sync(const unsigned long long handle)
|
451 |
+
{
|
452 |
+
cudaError_t err = cudaCGSynchronize(handle, 0);
|
453 |
+
}
|
454 |
+
|
455 |
+
_CG_STATIC_QUALIFIER unsigned int size(const unsigned long long handle)
|
456 |
+
{
|
457 |
+
unsigned int numThreads = 0;
|
458 |
+
cudaCGGetSize(&numThreads, NULL, handle);
|
459 |
+
return numThreads;
|
460 |
+
}
|
461 |
+
|
462 |
+
_CG_STATIC_QUALIFIER unsigned int thread_rank(const unsigned long long handle)
|
463 |
+
{
|
464 |
+
unsigned int threadRank = 0;
|
465 |
+
cudaCGGetRank(&threadRank, NULL, handle);
|
466 |
+
return threadRank;
|
467 |
+
}
|
468 |
+
|
469 |
+
_CG_STATIC_QUALIFIER unsigned int grid_rank(const unsigned long long handle)
|
470 |
+
{
|
471 |
+
unsigned int gridRank = 0;
|
472 |
+
cudaCGGetRank(NULL, &gridRank, handle);
|
473 |
+
return gridRank;
|
474 |
+
}
|
475 |
+
|
476 |
+
_CG_STATIC_QUALIFIER unsigned int num_grids(const unsigned long long handle)
|
477 |
+
{
|
478 |
+
unsigned int numGrids = 0;
|
479 |
+
cudaCGGetSize(NULL, &numGrids, handle);
|
480 |
+
return numGrids;
|
481 |
+
}
|
482 |
+
|
483 |
+
# ifdef _CG_CPP11_FEATURES
|
484 |
+
struct multi_grid_functions {
|
485 |
+
decltype(multi_grid::get_intrinsic_handle) *get_intrinsic_handle;
|
486 |
+
decltype(multi_grid::sync) *sync;
|
487 |
+
decltype(multi_grid::size) *size;
|
488 |
+
decltype(multi_grid::thread_rank) *thread_rank;
|
489 |
+
decltype(multi_grid::grid_rank) *grid_rank;
|
490 |
+
decltype(multi_grid::num_grids) *num_grids;
|
491 |
+
};
|
492 |
+
|
493 |
+
template <typename = void>
|
494 |
+
_CG_STATIC_QUALIFIER const multi_grid_functions* load_grid_intrinsics() {
|
495 |
+
__constant__ static const multi_grid_functions mgf {
|
496 |
+
&multi_grid::get_intrinsic_handle,
|
497 |
+
&multi_grid::sync,
|
498 |
+
&multi_grid::size,
|
499 |
+
&multi_grid::thread_rank,
|
500 |
+
&multi_grid::grid_rank,
|
501 |
+
&multi_grid::num_grids
|
502 |
+
};
|
503 |
+
|
504 |
+
return &mgf;
|
505 |
+
}
|
506 |
+
# endif
|
507 |
+
};
|
508 |
+
#endif
|
509 |
+
|
510 |
+
#if defined(_CG_HAS_CLUSTER_GROUP)
|
511 |
+
namespace cluster {
|
512 |
+
|
513 |
+
_CG_STATIC_QUALIFIER bool isReal()
|
514 |
+
{
|
515 |
+
return __clusterDimIsSpecified();
|
516 |
+
}
|
517 |
+
|
518 |
+
_CG_STATIC_QUALIFIER void barrier_arrive()
|
519 |
+
{
|
520 |
+
__cluster_barrier_arrive();
|
521 |
+
}
|
522 |
+
|
523 |
+
_CG_STATIC_QUALIFIER void barrier_wait()
|
524 |
+
{
|
525 |
+
__cluster_barrier_wait();
|
526 |
+
}
|
527 |
+
|
528 |
+
_CG_STATIC_QUALIFIER void sync()
|
529 |
+
{
|
530 |
+
barrier_arrive();
|
531 |
+
barrier_wait();
|
532 |
+
}
|
533 |
+
|
534 |
+
_CG_STATIC_QUALIFIER unsigned int query_shared_rank(const void *addr)
|
535 |
+
{
|
536 |
+
return __cluster_query_shared_rank(addr);
|
537 |
+
}
|
538 |
+
|
539 |
+
template <typename T>
|
540 |
+
_CG_STATIC_QUALIFIER T* map_shared_rank(T *addr, int rank)
|
541 |
+
{
|
542 |
+
return static_cast<T*>(__cluster_map_shared_rank(addr, rank));
|
543 |
+
}
|
544 |
+
|
545 |
+
_CG_STATIC_QUALIFIER dim3 block_index()
|
546 |
+
{
|
547 |
+
return __clusterRelativeBlockIdx();
|
548 |
+
}
|
549 |
+
|
550 |
+
_CG_STATIC_QUALIFIER unsigned int block_rank()
|
551 |
+
{
|
552 |
+
return __clusterRelativeBlockRank();
|
553 |
+
}
|
554 |
+
|
555 |
+
_CG_STATIC_QUALIFIER unsigned int thread_rank()
|
556 |
+
{
|
557 |
+
return block_rank() * cta::num_threads() + cta::thread_rank();
|
558 |
+
}
|
559 |
+
|
560 |
+
_CG_STATIC_QUALIFIER dim3 dim_blocks()
|
561 |
+
{
|
562 |
+
return __clusterDim();
|
563 |
+
}
|
564 |
+
|
565 |
+
_CG_STATIC_QUALIFIER unsigned int num_blocks()
|
566 |
+
{
|
567 |
+
return __clusterSizeInBlocks();
|
568 |
+
}
|
569 |
+
|
570 |
+
_CG_STATIC_QUALIFIER dim3 dim_threads()
|
571 |
+
{
|
572 |
+
const dim3 dimBlocks = dim_blocks();
|
573 |
+
const unsigned int x = dimBlocks.x * blockDim.x;
|
574 |
+
const unsigned int y = dimBlocks.y * blockDim.y;
|
575 |
+
const unsigned int z = dimBlocks.z * blockDim.z;
|
576 |
+
return dim3(x, y, z);
|
577 |
+
}
|
578 |
+
|
579 |
+
_CG_STATIC_QUALIFIER unsigned int num_threads()
|
580 |
+
{
|
581 |
+
return num_blocks() * cta::num_threads();
|
582 |
+
}
|
583 |
+
|
584 |
+
};
|
585 |
+
#endif
|
586 |
+
|
587 |
+
_CG_STATIC_QUALIFIER unsigned int laneid()
|
588 |
+
{
|
589 |
+
unsigned int laneid;
|
590 |
+
asm ("mov.u32 %0, %%laneid;" : "=r"(laneid));
|
591 |
+
return laneid;
|
592 |
+
}
|
593 |
+
|
594 |
+
_CG_STATIC_QUALIFIER unsigned int lanemask32_eq()
|
595 |
+
{
|
596 |
+
unsigned int lanemask32_eq;
|
597 |
+
asm ("mov.u32 %0, %%lanemask_eq;" : "=r"(lanemask32_eq));
|
598 |
+
return (lanemask32_eq);
|
599 |
+
}
|
600 |
+
|
601 |
+
_CG_STATIC_QUALIFIER unsigned int lanemask32_lt()
|
602 |
+
{
|
603 |
+
unsigned int lanemask32_lt;
|
604 |
+
asm ("mov.u32 %0, %%lanemask_lt;" : "=r"(lanemask32_lt));
|
605 |
+
return (lanemask32_lt);
|
606 |
+
}
|
607 |
+
|
608 |
+
_CG_STATIC_QUALIFIER void abort()
|
609 |
+
{
|
610 |
+
_CG_ABORT();
|
611 |
+
}
|
612 |
+
|
613 |
+
template <typename Ty>
|
614 |
+
_CG_QUALIFIER void assert_if_not_arithmetic() {
|
615 |
+
#ifdef _CG_CPP11_FEATURES
|
616 |
+
static_assert(
|
617 |
+
_CG_STL_NAMESPACE::is_integral<Ty>::value ||
|
618 |
+
details::is_float_or_half<Ty>::value,
|
619 |
+
"Error: Ty is neither integer or float"
|
620 |
+
);
|
621 |
+
#endif //_CG_CPP11_FEATURES
|
622 |
+
}
|
623 |
+
|
624 |
+
#ifdef _CG_CPP11_FEATURES
|
625 |
+
_CG_STATIC_QUALIFIER constexpr unsigned int log2(unsigned int x) {
|
626 |
+
return x == 1 ? 0 : 1 + log2(x / 2);
|
627 |
+
}
|
628 |
+
#endif //_CG_CPP11_FEATURES
|
629 |
+
|
630 |
+
}; // !Namespace internal
|
631 |
+
|
632 |
+
_CG_END_NAMESPACE
|
633 |
+
|
634 |
+
#endif /* !_COOPERATIVE_GROUPS_HELPERS_H_ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/info.h
ADDED
@@ -0,0 +1,338 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
1 |
+
/* Copyright 1993-2021 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
|
50 |
+
|
51 |
+
#ifndef _CG_INFO_H_
|
52 |
+
#define _CG_INFO_H_
|
53 |
+
/*
|
54 |
+
** Define: _CG_VERSION
|
55 |
+
*/
|
56 |
+
#define _CG_VERSION 1000
|
57 |
+
|
58 |
+
/*
|
59 |
+
** Define: _CG_ABI_VERSION
|
60 |
+
*/
|
61 |
+
#ifndef _CG_ABI_VERSION
|
62 |
+
# define _CG_ABI_VERSION 1
|
63 |
+
#endif
|
64 |
+
|
65 |
+
/*
|
66 |
+
** Define: _CG_ABI_EXPERIMENTAL
|
67 |
+
** Desc: If enabled, sets all features enabled (ABI-breaking or experimental)
|
68 |
+
*/
|
69 |
+
#if defined(_CG_ABI_EXPERIMENTAL)
|
70 |
+
#endif
|
71 |
+
|
72 |
+
#define _CG_CONCAT_INNER(x, y) x ## y
|
73 |
+
#define _CG_CONCAT_OUTER(x, y) _CG_CONCAT_INNER(x, y)
|
74 |
+
#define _CG_NAMESPACE _CG_CONCAT_OUTER(__v, _CG_ABI_VERSION)
|
75 |
+
|
76 |
+
#define _CG_BEGIN_NAMESPACE \
|
77 |
+
namespace cooperative_groups { namespace _CG_NAMESPACE {
|
78 |
+
#define _CG_END_NAMESPACE \
|
79 |
+
}; using namespace _CG_NAMESPACE; };
|
80 |
+
|
81 |
+
#if (defined(__cplusplus) && (__cplusplus >= 201103L)) || (defined(_MSC_VER) && (_MSC_VER >= 1900))
|
82 |
+
# define _CG_CPP11_FEATURES
|
83 |
+
#endif
|
84 |
+
|
85 |
+
#if !defined(_CG_QUALIFIER)
|
86 |
+
# define _CG_QUALIFIER __forceinline__ __device__
|
87 |
+
#endif
|
88 |
+
#if !defined(_CG_STATIC_QUALIFIER)
|
89 |
+
# define _CG_STATIC_QUALIFIER static __forceinline__ __device__
|
90 |
+
#endif
|
91 |
+
#if !defined(_CG_CONSTEXPR_QUALIFIER)
|
92 |
+
# if defined(_CG_CPP11_FEATURES)
|
93 |
+
# define _CG_CONSTEXPR_QUALIFIER constexpr __forceinline__ __device__
|
94 |
+
# else
|
95 |
+
# define _CG_CONSTEXPR_QUALIFIER _CG_QUALIFIER
|
96 |
+
# endif
|
97 |
+
#endif
|
98 |
+
#if !defined(_CG_STATIC_CONSTEXPR_QUALIFIER)
|
99 |
+
# if defined(_CG_CPP11_FEATURES)
|
100 |
+
# define _CG_STATIC_CONSTEXPR_QUALIFIER static constexpr __forceinline__ __device__
|
101 |
+
# else
|
102 |
+
# define _CG_STATIC_CONSTEXPR_QUALIFIER _CG_STATIC_QUALIFIER
|
103 |
+
# endif
|
104 |
+
#endif
|
105 |
+
|
106 |
+
#if defined(_MSC_VER)
|
107 |
+
# define _CG_DEPRECATED __declspec(deprecated)
|
108 |
+
#else
|
109 |
+
# define _CG_DEPRECATED __attribute__((deprecated))
|
110 |
+
#endif
|
111 |
+
|
112 |
+
#if (__CUDA_ARCH__ >= 600) || !defined(__CUDA_ARCH__)
|
113 |
+
# define _CG_HAS_GRID_GROUP
|
114 |
+
#endif
|
115 |
+
#if (__CUDA_ARCH__ >= 600) || !defined(__CUDA_ARCH__)
|
116 |
+
# define _CG_HAS_MULTI_GRID_GROUP
|
117 |
+
#endif
|
118 |
+
#if (__CUDA_ARCH__ >= 700) || !defined(__CUDA_ARCH__)
|
119 |
+
# define _CG_HAS_MATCH_COLLECTIVE
|
120 |
+
#endif
|
121 |
+
|
122 |
+
#if (__CUDA_ARCH__ >= 800) || !defined(__CUDA_ARCH__) && (defined(__NVCC__) || defined(__CUDACC_RTC__))
|
123 |
+
# define _CG_HAS_OP_REDUX
|
124 |
+
#endif
|
125 |
+
|
126 |
+
#if ((__CUDA_ARCH__ >= 800) || !defined(__CUDA_ARCH__)) && !defined(_CG_USER_PROVIDED_SHARED_MEMORY)
|
127 |
+
# define _CG_HAS_RESERVED_SHARED
|
128 |
+
#endif
|
129 |
+
|
130 |
+
#if ((__CUDA_ARCH__ >= 900) || !defined(__CUDA_ARCH__)) && \
|
131 |
+
(defined(__NVCC__) || defined(__CUDACC_RTC__) || defined(_CG_CLUSTER_INTRINSICS_AVAILABLE)) && \
|
132 |
+
defined(_CG_CPP11_FEATURES)
|
133 |
+
# define _CG_HAS_CLUSTER_GROUP
|
134 |
+
#endif
|
135 |
+
|
136 |
+
#if (__CUDA_ARCH__ >= 900) || !defined(__CUDA_ARCH__)
|
137 |
+
# define _CG_HAS_INSTR_ELECT
|
138 |
+
#endif
|
139 |
+
|
140 |
+
// Has __half and __half2
|
141 |
+
// Only usable if you include the cuda_fp16.h extension, and
|
142 |
+
// _before_ including cooperative_groups.h
|
143 |
+
#ifdef __CUDA_FP16_TYPES_EXIST__
|
144 |
+
# define _CG_HAS_FP16_COLLECTIVE
|
145 |
+
#endif
|
146 |
+
|
147 |
+
// Include libcu++ where supported.
|
148 |
+
#if defined(_CG_CPP11_FEATURES) && !defined(__QNX__) && !defined(__ibmxl__) && \
|
149 |
+
(defined(__NVCC__) || defined(__CUDACC_RTC__)) && \
|
150 |
+
(defined(__x86_64__) || defined(__aarch64__) || defined(__ppc64__)|| defined(_M_X64) || defined(_M_ARM64)) && \
|
151 |
+
(defined(_MSC_VER) || defined(__GNUC__) || defined(__clang__))
|
152 |
+
# define _CG_USE_CUDA_STL
|
153 |
+
#else
|
154 |
+
# define _CG_USE_OWN_TRAITS
|
155 |
+
#endif
|
156 |
+
|
157 |
+
#if defined(_CG_USE_CUDA_STL) && (!defined(__CUDA_ARCH__) || \
|
158 |
+
((!defined(_MSC_VER) && __CUDA_ARCH__ >= 600) || (defined(_MSC_VER) && __CUDA_ARCH__ >= 700)))
|
159 |
+
# define _CG_HAS_STL_ATOMICS
|
160 |
+
#endif
|
161 |
+
|
162 |
+
#ifdef _CG_CPP11_FEATURES
|
163 |
+
// Use cuda::std:: for type_traits
|
164 |
+
# if defined(_CG_USE_CUDA_STL)
|
165 |
+
# define _CG_STL_NAMESPACE cuda::std
|
166 |
+
# include <cuda/std/type_traits>
|
167 |
+
// Use CG's implementation of type traits
|
168 |
+
# else
|
169 |
+
# define _CG_STL_NAMESPACE cooperative_groups::details::templates
|
170 |
+
# endif
|
171 |
+
#endif
|
172 |
+
|
173 |
+
#ifdef _CG_CPP11_FEATURES
|
174 |
+
# define _CG_STATIC_CONST_DECL static constexpr
|
175 |
+
# define _CG_CONST_DECL constexpr
|
176 |
+
#else
|
177 |
+
# define _CG_STATIC_CONST_DECL static const
|
178 |
+
# define _CG_CONST_DECL const
|
179 |
+
#endif
|
180 |
+
|
181 |
+
#if (defined(_MSC_VER) && !defined(_WIN64)) || defined(__arm__)
|
182 |
+
# define _CG_ASM_PTR_CONSTRAINT "r"
|
183 |
+
#else
|
184 |
+
# define _CG_ASM_PTR_CONSTRAINT "l"
|
185 |
+
#endif
|
186 |
+
|
187 |
+
/*
|
188 |
+
** Define: CG_DEBUG
|
189 |
+
** What: Enables various runtime safety checks
|
190 |
+
*/
|
191 |
+
#if defined(__CUDACC_DEBUG__) && defined(CG_DEBUG) && !defined(NDEBUG)
|
192 |
+
# define _CG_DEBUG
|
193 |
+
#endif
|
194 |
+
|
195 |
+
#if defined(_CG_DEBUG)
|
196 |
+
# include <assert.h>
|
197 |
+
# define _CG_ASSERT(x) assert((x));
|
198 |
+
# define _CG_ABORT() assert(0);
|
199 |
+
#else
|
200 |
+
# define _CG_ASSERT(x)
|
201 |
+
# define _CG_ABORT() __trap();
|
202 |
+
#endif
|
203 |
+
|
204 |
+
_CG_BEGIN_NAMESPACE
|
205 |
+
|
206 |
+
namespace details {
|
207 |
+
_CG_STATIC_CONST_DECL unsigned int default_max_block_size = 1024;
|
208 |
+
|
209 |
+
#if defined(_CG_CPP11_FEATURES) && !defined(_CG_USE_CUDA_STL)
|
210 |
+
namespace templates {
|
211 |
+
|
212 |
+
/**
|
213 |
+
* Integral constants
|
214 |
+
**/
|
215 |
+
template <typename Ty, Ty Val>
|
216 |
+
struct integral_constant {
|
217 |
+
static constexpr Ty value = Val;
|
218 |
+
typedef Ty type;
|
219 |
+
|
220 |
+
_CG_QUALIFIER constexpr operator type() const noexcept { return value; }
|
221 |
+
_CG_QUALIFIER constexpr type operator()() const noexcept { return value; }
|
222 |
+
};
|
223 |
+
|
224 |
+
typedef integral_constant<bool, true> true_type;
|
225 |
+
typedef integral_constant<bool, false> false_type;
|
226 |
+
|
227 |
+
/**
|
228 |
+
* CV Qualifiers
|
229 |
+
**/
|
230 |
+
template <class Ty> struct is_lvalue_reference : public details::templates::false_type {};
|
231 |
+
template <class Ty> struct is_lvalue_reference<Ty&> : public details::templates::true_type {};
|
232 |
+
|
233 |
+
template <class Ty> struct remove_reference {typedef Ty type;};
|
234 |
+
template <class Ty> struct remove_reference<Ty&> {typedef Ty type;};
|
235 |
+
template <class Ty> struct remove_reference<Ty&&> {typedef Ty type;};
|
236 |
+
|
237 |
+
template <class Ty>
|
238 |
+
using remove_reference_t = typename details::templates::remove_reference<Ty>::type;
|
239 |
+
|
240 |
+
template <class Ty> struct remove_const {typedef Ty type;};
|
241 |
+
template <class Ty> struct remove_const<const Ty> {typedef Ty type;};
|
242 |
+
|
243 |
+
template <class Ty> struct remove_volatile {typedef Ty type;};
|
244 |
+
template <class Ty> struct remove_volatile<volatile Ty> {typedef Ty type;};
|
245 |
+
|
246 |
+
template <class Ty> struct remove_cv {typedef typename details::templates::remove_volatile<typename details::templates::remove_const<Ty>::type>::type type;};
|
247 |
+
|
248 |
+
template <class Ty>
|
249 |
+
using remove_cv_t = typename details::templates::remove_cv<Ty>::type;
|
250 |
+
|
251 |
+
template <class Ty>
|
252 |
+
_CG_QUALIFIER Ty&& forward(remove_reference_t<Ty> &t) noexcept {
|
253 |
+
return static_cast<Ty&&>(t);
|
254 |
+
}
|
255 |
+
|
256 |
+
template <class Ty>
|
257 |
+
_CG_QUALIFIER Ty&& forward(remove_reference_t<Ty> &&t) noexcept {
|
258 |
+
static_assert(!details::templates::is_lvalue_reference<Ty>::value, "Forwarding an rvalue as an lvalue is not allowed.");
|
259 |
+
return static_cast<Ty&&>(t);
|
260 |
+
}
|
261 |
+
|
262 |
+
/**
|
263 |
+
* is_integral
|
264 |
+
**/
|
265 |
+
template <class Ty> struct _is_integral : public details::templates::false_type {};
|
266 |
+
template <> struct _is_integral<bool> : public details::templates::true_type {};
|
267 |
+
template <> struct _is_integral<char> : public details::templates::true_type {};
|
268 |
+
template <> struct _is_integral<unsigned char> : public details::templates::true_type {};
|
269 |
+
template <> struct _is_integral<short> : public details::templates::true_type {};
|
270 |
+
template <> struct _is_integral<unsigned short> : public details::templates::true_type {};
|
271 |
+
template <> struct _is_integral<int> : public details::templates::true_type {};
|
272 |
+
template <> struct _is_integral<unsigned int> : public details::templates::true_type {};
|
273 |
+
template <> struct _is_integral<long> : public details::templates::true_type {};
|
274 |
+
template <> struct _is_integral<long long> : public details::templates::true_type {};
|
275 |
+
template <> struct _is_integral<unsigned long> : public details::templates::true_type {};
|
276 |
+
template <> struct _is_integral<unsigned long long> : public details::templates::true_type {};
|
277 |
+
//Vector type support?
|
278 |
+
|
279 |
+
template <typename Ty>
|
280 |
+
struct is_integral : public details::templates::_is_integral<typename details::templates::remove_cv<Ty>::type> {};
|
281 |
+
|
282 |
+
/**
|
283 |
+
* is_floating_point
|
284 |
+
**/
|
285 |
+
template <class Ty> struct _is_floating_point : public details::templates::false_type {};
|
286 |
+
template <> struct _is_floating_point<float> : public details::templates::true_type {};
|
287 |
+
template <> struct _is_floating_point<double> : public details::templates::true_type {};
|
288 |
+
template <> struct _is_floating_point<long double> : public details::templates::true_type {};
|
289 |
+
# ifdef __CUDA_FP16_TYPES_EXIST__
|
290 |
+
template <> struct _is_floating_point<__half> : public details::templates::true_type {};
|
291 |
+
template <> struct _is_floating_point<__half2> : public details::templates::true_type {};
|
292 |
+
# endif
|
293 |
+
//Vector type support?
|
294 |
+
|
295 |
+
template <typename Ty>
|
296 |
+
struct is_floating_point : public details::templates::_is_floating_point<typename details::templates::remove_cv<Ty>::type> {};
|
297 |
+
|
298 |
+
template <class T>
|
299 |
+
struct is_arithmetic : details::templates::integral_constant<
|
300 |
+
bool,
|
301 |
+
details::templates::is_integral<T>::value ||
|
302 |
+
details::templates::is_floating_point<T>::value> {};
|
303 |
+
|
304 |
+
template <typename Ty, bool = details::templates::is_arithmetic<Ty>::value>
|
305 |
+
struct _is_unsigned : details::templates::integral_constant<bool, Ty(0) < Ty(-1)> {};
|
306 |
+
|
307 |
+
template <typename Ty>
|
308 |
+
struct _is_unsigned<Ty,false> : details::templates::false_type {};
|
309 |
+
|
310 |
+
template <typename Ty>
|
311 |
+
struct is_unsigned : _is_unsigned<typename details::templates::remove_cv<Ty>::type> {};
|
312 |
+
|
313 |
+
/**
|
314 |
+
* programmatic type traits
|
315 |
+
**/
|
316 |
+
template<bool B, class Ty = void>
|
317 |
+
struct enable_if {};
|
318 |
+
|
319 |
+
template<class Ty>
|
320 |
+
struct enable_if<true, Ty> { typedef Ty type; };
|
321 |
+
|
322 |
+
template<bool Cond, typename Ty = void>
|
323 |
+
using enable_if_t = typename details::templates::enable_if<Cond, Ty>::type;
|
324 |
+
|
325 |
+
template<class Ty1, class Ty2>
|
326 |
+
struct is_same : details::templates::false_type {};
|
327 |
+
|
328 |
+
template<class Ty>
|
329 |
+
struct is_same<Ty, Ty> : details::templates::true_type {};
|
330 |
+
|
331 |
+
} // templates
|
332 |
+
#endif // _CG_CPP11_FEATURES
|
333 |
+
|
334 |
+
} // details
|
335 |
+
_CG_END_NAMESPACE
|
336 |
+
|
337 |
+
|
338 |
+
#endif // _CG_INFO_H_
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/invoke.h
ADDED
@@ -0,0 +1,189 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2022 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#ifndef _CG_INVOKE_H
|
51 |
+
#define _CG_INVOKE_H
|
52 |
+
|
53 |
+
#include "info.h"
|
54 |
+
#include "helpers.h"
|
55 |
+
|
56 |
+
#if defined(_CG_CPP11_FEATURES)
|
57 |
+
|
58 |
+
_CG_BEGIN_NAMESPACE
|
59 |
+
|
60 |
+
namespace details {
|
61 |
+
|
62 |
+
template <typename Group>
|
63 |
+
struct _elect_group_supported : _CG_STL_NAMESPACE::false_type {};
|
64 |
+
#ifdef _CG_HAS_INSTR_ELECT
|
65 |
+
template<>
|
66 |
+
struct _elect_group_supported<coalesced_group> : _CG_STL_NAMESPACE::true_type {};
|
67 |
+
template<unsigned int Size, typename Parent>
|
68 |
+
struct _elect_group_supported<thread_block_tile<Size, Parent>> :
|
69 |
+
_CG_STL_NAMESPACE::integral_constant<bool, (Size <= 32)> {};
|
70 |
+
#endif
|
71 |
+
|
72 |
+
template <typename Group>
|
73 |
+
struct elect_group_supported : public _elect_group_supported<details::remove_qual<Group>> {};
|
74 |
+
|
75 |
+
template<typename Group>
|
76 |
+
_CG_STATIC_QUALIFIER bool elect_one(const Group& group, unsigned int mask, unsigned int& leader_lane) {
|
77 |
+
int is_leader = 0;
|
78 |
+
#ifdef _CG_HAS_INSTR_ELECT
|
79 |
+
asm("{\n\t"
|
80 |
+
" .reg .pred p;\n\t"
|
81 |
+
" elect.sync %0|p, %2;\n\t"
|
82 |
+
" @p mov.s32 %1, 1;\n\t"
|
83 |
+
"}"
|
84 |
+
: "+r"(leader_lane), "+r"(is_leader) : "r" (mask));
|
85 |
+
#endif
|
86 |
+
return is_leader;
|
87 |
+
}
|
88 |
+
|
89 |
+
template<bool UseElect>
|
90 |
+
struct invoke_one_impl {};
|
91 |
+
|
92 |
+
template<>
|
93 |
+
struct invoke_one_impl<true> {
|
94 |
+
template<typename Group, typename Fn, typename... Args>
|
95 |
+
_CG_STATIC_QUALIFIER void invoke_one(const Group& group, Fn&& fn, Args&&... args) {
|
96 |
+
auto mask = details::_coalesced_group_data_access::get_mask(group);
|
97 |
+
unsigned int leader_lane = 0;
|
98 |
+
|
99 |
+
if (elect_one(group, mask, leader_lane)) {
|
100 |
+
_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
|
101 |
+
}
|
102 |
+
}
|
103 |
+
|
104 |
+
template<typename Group, typename Fn, typename... Args>
|
105 |
+
_CG_STATIC_QUALIFIER auto invoke_one_broadcast(const Group& group, Fn&& fn, Args&&... args)
|
106 |
+
-> typename _CG_STL_NAMESPACE::remove_reference<
|
107 |
+
decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
|
108 |
+
|
109 |
+
using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
|
110 |
+
details::remove_qual<ResultType> result;
|
111 |
+
auto mask = details::_coalesced_group_data_access::get_mask(group);
|
112 |
+
unsigned int leader_lane = 0;
|
113 |
+
|
114 |
+
if (elect_one(group, mask, leader_lane)) {
|
115 |
+
result = _CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
|
116 |
+
}
|
117 |
+
|
118 |
+
// Need to use low level api instead of group.shfl, because elect_one returns lane id, not group rank.
|
119 |
+
return tile::shuffle_dispatch<ResultType>::shfl(result, mask, leader_lane, 32);
|
120 |
+
}
|
121 |
+
};
|
122 |
+
|
123 |
+
template<>
|
124 |
+
struct invoke_one_impl<false> {
|
125 |
+
template<typename Group, typename Fn, typename... Args>
|
126 |
+
_CG_STATIC_QUALIFIER void invoke_one(const Group& group, Fn&& fn, Args&&... args) {
|
127 |
+
if (group.thread_rank() == 0) {
|
128 |
+
_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
|
129 |
+
}
|
130 |
+
}
|
131 |
+
|
132 |
+
template<typename Group, typename Fn, typename... Args>
|
133 |
+
_CG_STATIC_QUALIFIER auto invoke_one_broadcast(const Group& group, Fn&& fn, Args&&... args)
|
134 |
+
-> typename _CG_STL_NAMESPACE::remove_reference<
|
135 |
+
decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
|
136 |
+
|
137 |
+
using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
|
138 |
+
details::remove_qual<ResultType> result;
|
139 |
+
|
140 |
+
if (group.thread_rank() == 0) {
|
141 |
+
result = _CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...);
|
142 |
+
}
|
143 |
+
|
144 |
+
return group.shfl(result, 0);
|
145 |
+
}
|
146 |
+
};
|
147 |
+
|
148 |
+
|
149 |
+
}; // namespace details
|
150 |
+
|
151 |
+
template<typename Group, typename Fn, typename... Args>
|
152 |
+
_CG_QUALIFIER void invoke_one(const Group& group, Fn&& fn, Args&&... args) {
|
153 |
+
using impl = details::invoke_one_impl<details::elect_group_supported<Group>::value>;
|
154 |
+
impl::invoke_one(group, _CG_STL_NAMESPACE::forward<Fn>(fn), _CG_STL_NAMESPACE::forward<Args>(args)...);
|
155 |
+
}
|
156 |
+
|
157 |
+
template<typename Fn, typename... Args>
|
158 |
+
_CG_QUALIFIER auto invoke_one_broadcast(const coalesced_group& group, Fn&& fn, Args&&... args)
|
159 |
+
-> typename _CG_STL_NAMESPACE::remove_reference<
|
160 |
+
decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
|
161 |
+
|
162 |
+
using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
|
163 |
+
static_assert(!_CG_STL_NAMESPACE::is_same<ResultType, void>::value,
|
164 |
+
"For invocables returning void invoke_one should be used instead");
|
165 |
+
using impl = details::invoke_one_impl<details::elect_group_supported<coalesced_group>::value>;
|
166 |
+
return impl::invoke_one_broadcast(group,
|
167 |
+
_CG_STL_NAMESPACE::forward<Fn>(fn),
|
168 |
+
_CG_STL_NAMESPACE::forward<Args>(args)...);
|
169 |
+
}
|
170 |
+
|
171 |
+
template<unsigned int Size, typename Parent, typename Fn, typename... Args>
|
172 |
+
_CG_QUALIFIER auto invoke_one_broadcast(const thread_block_tile<Size, Parent>& group, Fn&& fn, Args&&... args)
|
173 |
+
-> typename _CG_STL_NAMESPACE::remove_reference<
|
174 |
+
decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...))>::type {
|
175 |
+
|
176 |
+
using ResultType = decltype(_CG_STL_NAMESPACE::forward<Fn>(fn)(_CG_STL_NAMESPACE::forward<Args>(args)...));
|
177 |
+
static_assert(!_CG_STL_NAMESPACE::is_same<ResultType, void>::value,
|
178 |
+
"For invocables returning void invoke_one should be used instead");
|
179 |
+
using impl = details::invoke_one_impl<details::elect_group_supported<thread_block_tile<Size, Parent>>::value>;
|
180 |
+
return impl::invoke_one_broadcast(group,
|
181 |
+
_CG_STL_NAMESPACE::forward<Fn>(fn),
|
182 |
+
_CG_STL_NAMESPACE::forward<Args>(args)...);
|
183 |
+
}
|
184 |
+
|
185 |
+
_CG_END_NAMESPACE
|
186 |
+
|
187 |
+
#endif //_CG_CPP11_FEATURES
|
188 |
+
|
189 |
+
#endif // _CG_INVOKE_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/memory.h
ADDED
@@ -0,0 +1,135 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2022 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _COOPERATIVE_GROUPS_MEMORY_H_
|
50 |
+
# define _COOPERATIVE_GROUPS_MEMORY_H_
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
|
54 |
+
_CG_BEGIN_NAMESPACE
|
55 |
+
|
56 |
+
#if defined(_CG_CPP11_FEATURES)
|
57 |
+
namespace details {
|
58 |
+
_CG_STATIC_CONST_DECL int scratch_num_reserved_bytes = 12;
|
59 |
+
|
60 |
+
#if defined(_CG_HAS_RESERVED_SHARED)
|
61 |
+
_CG_STATIC_QUALIFIER void* reserved_shared_ptr()
|
62 |
+
{
|
63 |
+
void *ptr;
|
64 |
+
asm ("{\n\t"
|
65 |
+
" .reg .u32 start;\n\t"
|
66 |
+
" .reg .u64 extended;\n\t"
|
67 |
+
" mov.u32 start, %%reserved_smem_offset_1;\n\t"
|
68 |
+
" cvt.u64.u32 extended, start;\n\t"
|
69 |
+
" cvta.shared.u64 %0, extended;\n\t"
|
70 |
+
"}"
|
71 |
+
: "=" _CG_ASM_PTR_CONSTRAINT(ptr));
|
72 |
+
return ptr;
|
73 |
+
}
|
74 |
+
#endif
|
75 |
+
|
76 |
+
struct multi_warp_scratch {
|
77 |
+
// One barrier per possible size of the group.
|
78 |
+
_CG_STATIC_CONST_DECL unsigned int memory_barriers_count = 5;
|
79 |
+
_CG_STATIC_CONST_DECL size_t sync_memory_size = memory_barriers_count * sizeof(barrier_t);
|
80 |
+
|
81 |
+
using communication_type = unsigned long long;
|
82 |
+
_CG_STATIC_CONST_DECL size_t communication_size = sizeof(communication_type);
|
83 |
+
|
84 |
+
// Layout of the scratch space:
|
85 |
+
barrier_t barriers[memory_barriers_count];
|
86 |
+
char reserved[scratch_num_reserved_bytes]; // Reserve 12 bytes for future use
|
87 |
+
communication_type communication_memory[default_max_block_size / 32];
|
88 |
+
|
89 |
+
_CG_STATIC_CONSTEXPR_QUALIFIER unsigned int scratch_size_needed(unsigned int max_block_size) {
|
90 |
+
// One slot of collectives memory per warp.
|
91 |
+
return scratch_num_reserved_bytes + sync_memory_size + max_block_size / 32 * communication_size;
|
92 |
+
}
|
93 |
+
|
94 |
+
_CG_QUALIFIER void init_barriers(unsigned int thread_rank) {
|
95 |
+
if (thread_rank < memory_barriers_count) {
|
96 |
+
barriers[thread_rank] = 0;
|
97 |
+
}
|
98 |
+
}
|
99 |
+
};
|
100 |
+
|
101 |
+
#if defined(_CG_HAS_RESERVED_SHARED)
|
102 |
+
// CG can expect at least 288 bytes available in reserved shared
|
103 |
+
static_assert(sizeof(multi_warp_scratch) <= 288, "multi-warp scratch size is too large");
|
104 |
+
#endif
|
105 |
+
|
106 |
+
// Make sure the structure can fit into the user provided memory
|
107 |
+
static_assert(sizeof(multi_warp_scratch) <= multi_warp_scratch::scratch_size_needed(default_max_block_size),
|
108 |
+
"multi-warp scratch size is too large");
|
109 |
+
|
110 |
+
|
111 |
+
_CG_QUALIFIER multi_warp_scratch* get_scratch_ptr(void* user_scratch) {
|
112 |
+
void *ptr;
|
113 |
+
#if defined(_CG_HAS_RESERVED_SHARED)
|
114 |
+
ptr = reserved_shared_ptr();
|
115 |
+
#else
|
116 |
+
ptr = user_scratch;
|
117 |
+
#endif
|
118 |
+
return static_cast<multi_warp_scratch*>(ptr);
|
119 |
+
|
120 |
+
}
|
121 |
+
|
122 |
+
}
|
123 |
+
|
124 |
+
template <unsigned int MaxBlockSize = details::default_max_block_size>
|
125 |
+
struct __align__(details::multi_warp_scratch::communication_size) block_tile_memory {
|
126 |
+
private:
|
127 |
+
#if !defined(_CG_HAS_RESERVED_SHARED)
|
128 |
+
char scratch[details::multi_warp_scratch::scratch_size_needed(MaxBlockSize)];
|
129 |
+
#endif
|
130 |
+
};
|
131 |
+
#endif
|
132 |
+
|
133 |
+
_CG_END_NAMESPACE
|
134 |
+
|
135 |
+
#endif /* !_COOPERATIVE_GROUPS_MEMORY_H_ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/partitioning.h
ADDED
@@ -0,0 +1,133 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#ifndef _CG_PARTITIONING_H
|
51 |
+
#define _CG_PARTITIONING_H
|
52 |
+
|
53 |
+
#include "info.h"
|
54 |
+
#include "helpers.h"
|
55 |
+
|
56 |
+
_CG_BEGIN_NAMESPACE
|
57 |
+
|
58 |
+
namespace details {
|
59 |
+
|
60 |
+
template <typename TyGroup>
|
61 |
+
_CG_STATIC_QUALIFIER coalesced_group _binary_partition(const TyGroup &tile, bool pred) {
|
62 |
+
const unsigned int fullMask = ~0u;
|
63 |
+
|
64 |
+
unsigned int thisMask = _coalesced_group_data_access::get_mask(tile);
|
65 |
+
unsigned int predMask = pred ? 0 : fullMask;
|
66 |
+
unsigned int setMask = __ballot_sync(thisMask, pred);
|
67 |
+
|
68 |
+
if (setMask == thisMask || setMask == 0) {
|
69 |
+
coalesced_group subTile = _coalesced_group_data_access::construct_from_mask<coalesced_group>(thisMask);
|
70 |
+
_coalesced_group_data_access::modify_meta_group(subTile, 0, 1);
|
71 |
+
return subTile;
|
72 |
+
}
|
73 |
+
else {
|
74 |
+
unsigned int subMask = thisMask & (setMask ^ predMask);
|
75 |
+
coalesced_group subTile = _coalesced_group_data_access::construct_from_mask<coalesced_group>(subMask);
|
76 |
+
_coalesced_group_data_access::modify_meta_group(subTile, pred, 2);
|
77 |
+
return subTile;
|
78 |
+
}
|
79 |
+
}
|
80 |
+
|
81 |
+
#ifdef _CG_HAS_MATCH_COLLECTIVE
|
82 |
+
template <typename TyGroup, typename TyPredicate>
|
83 |
+
_CG_STATIC_QUALIFIER coalesced_group _labeled_partition(const TyGroup &tile, TyPredicate pred) {
|
84 |
+
unsigned int thisMask = _coalesced_group_data_access::get_mask(tile);
|
85 |
+
unsigned int thisBias = __ffs(thisMask) - 1; // Subtract 1 to index properly from [1-32]
|
86 |
+
unsigned int subMask = __match_any_sync(thisMask, pred);
|
87 |
+
|
88 |
+
coalesced_group subTile = _coalesced_group_data_access::construct_from_mask<coalesced_group>(subMask);
|
89 |
+
|
90 |
+
int leaderLaneId = subTile.shfl(details::laneid(), 0);
|
91 |
+
|
92 |
+
bool isLeader = !subTile.thread_rank();
|
93 |
+
unsigned int leaderMask = __ballot_sync(thisMask, isLeader);
|
94 |
+
unsigned int tileRank = __fns(leaderMask, leaderLaneId, 0) - thisBias;
|
95 |
+
|
96 |
+
_coalesced_group_data_access::modify_meta_group(subTile, tileRank, __popc(leaderMask));
|
97 |
+
|
98 |
+
return subTile;
|
99 |
+
}
|
100 |
+
#endif
|
101 |
+
}; // namespace details
|
102 |
+
|
103 |
+
_CG_STATIC_QUALIFIER coalesced_group binary_partition(const coalesced_group &tile, bool pred) {
|
104 |
+
return details::_binary_partition(tile, pred);
|
105 |
+
}
|
106 |
+
|
107 |
+
template <unsigned int Size, typename ParentT>
|
108 |
+
_CG_STATIC_QUALIFIER coalesced_group binary_partition(const thread_block_tile<Size, ParentT> &tile, bool pred) {
|
109 |
+
#ifdef _CG_CPP11_FEATURES
|
110 |
+
static_assert(Size <= 32, "Binary partition is available only for tiles of size smaller or equal to 32");
|
111 |
+
#endif
|
112 |
+
return details::_binary_partition(tile, pred);
|
113 |
+
}
|
114 |
+
|
115 |
+
|
116 |
+
#if defined(_CG_HAS_MATCH_COLLECTIVE) && defined(_CG_CPP11_FEATURES)
|
117 |
+
template <typename TyPredicate>
|
118 |
+
_CG_STATIC_QUALIFIER coalesced_group labeled_partition(const coalesced_group &tile, TyPredicate pred) {
|
119 |
+
static_assert(_CG_STL_NAMESPACE::is_integral<TyPredicate>::value, "labeled_partition predicate must be an integral type");
|
120 |
+
return details::_labeled_partition(tile, pred);
|
121 |
+
}
|
122 |
+
|
123 |
+
template <typename TyPredicate, unsigned int Size, typename ParentT>
|
124 |
+
_CG_STATIC_QUALIFIER coalesced_group labeled_partition(const thread_block_tile<Size, ParentT> &tile, TyPredicate pred) {
|
125 |
+
static_assert(_CG_STL_NAMESPACE::is_integral<TyPredicate>::value, "labeled_partition predicate must be an integral type");
|
126 |
+
static_assert(Size <= 32, "Labeled partition is available only for tiles of size smaller or equal to 32");
|
127 |
+
return details::_labeled_partition(tile, pred);
|
128 |
+
}
|
129 |
+
#endif
|
130 |
+
|
131 |
+
_CG_END_NAMESPACE
|
132 |
+
|
133 |
+
#endif // _CG_PARTITIONING_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/reduce.h
ADDED
@@ -0,0 +1,429 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_REDUCE_H_
|
50 |
+
#define _CG_REDUCE_H_
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
#include "helpers.h"
|
54 |
+
#include "coalesced_reduce.h"
|
55 |
+
#include "functional.h"
|
56 |
+
#include "cooperative_groups.h"
|
57 |
+
|
58 |
+
_CG_BEGIN_NAMESPACE
|
59 |
+
|
60 |
+
namespace details {
|
61 |
+
|
62 |
+
template <class Ty>
|
63 |
+
using _redux_is_add_supported = _CG_STL_NAMESPACE::integral_constant<
|
64 |
+
bool,
|
65 |
+
_CG_STL_NAMESPACE::is_integral<Ty>::value && (sizeof(Ty) <= 4)>;
|
66 |
+
|
67 |
+
template <class Ty>
|
68 |
+
using redux_is_add_supported = _redux_is_add_supported<Ty>;
|
69 |
+
|
70 |
+
// A specialization for 64 bit logical operations is possible
|
71 |
+
// but for now only accelerate 32 bit bitwise ops
|
72 |
+
template <class Ty>
|
73 |
+
using redux_is_logical_supported = redux_is_add_supported<Ty>;
|
74 |
+
|
75 |
+
// Base operator support case
|
76 |
+
template <class TyOp, class Ty> struct _redux_op_supported : public _CG_STL_NAMESPACE::false_type {};
|
77 |
+
#ifdef _CG_HAS_OP_REDUX
|
78 |
+
template <class Ty> struct _redux_op_supported<cooperative_groups::plus<Ty>, Ty> : public redux_is_add_supported<Ty> {};
|
79 |
+
template <class Ty> struct _redux_op_supported<cooperative_groups::less<Ty>, Ty> : public redux_is_add_supported<Ty> {};
|
80 |
+
template <class Ty> struct _redux_op_supported<cooperative_groups::greater<Ty>, Ty> : public redux_is_add_supported<Ty> {};
|
81 |
+
template <class Ty> struct _redux_op_supported<cooperative_groups::bit_and<Ty>, Ty> : public redux_is_logical_supported<Ty> {};
|
82 |
+
template <class Ty> struct _redux_op_supported<cooperative_groups::bit_or<Ty>, Ty> : public redux_is_logical_supported<Ty> {};
|
83 |
+
template <class Ty> struct _redux_op_supported<cooperative_groups::bit_xor<Ty>, Ty> : public redux_is_logical_supported<Ty> {};
|
84 |
+
#endif
|
85 |
+
|
86 |
+
template <class Ty, template <class> class TyOp>
|
87 |
+
using redux_op_supported = _redux_op_supported<
|
88 |
+
typename details::remove_qual<TyOp<Ty>>,
|
89 |
+
Ty>;
|
90 |
+
|
91 |
+
// Groups smaller than 16 actually have worse performance characteristics when used with redux
|
92 |
+
// tiles of size 16 and 32 perform the same or better and have better code generation profiles
|
93 |
+
template <class TyGroup> struct _redux_group_optimized : public _CG_STL_NAMESPACE::false_type {};
|
94 |
+
|
95 |
+
template <unsigned int Sz, typename TyPar>
|
96 |
+
struct _redux_group_optimized<cooperative_groups::thread_block_tile<Sz, TyPar>> : public _CG_STL_NAMESPACE::integral_constant<
|
97 |
+
bool,
|
98 |
+
(Sz >= 16)> {};
|
99 |
+
template <unsigned int Sz, typename TyPar>
|
100 |
+
struct _redux_group_optimized<internal_thread_block_tile<Sz, TyPar>> : public _CG_STL_NAMESPACE::integral_constant<
|
101 |
+
bool,
|
102 |
+
(Sz >= 16)> {};
|
103 |
+
template <>
|
104 |
+
struct _redux_group_optimized<cooperative_groups::coalesced_group> : public _CG_STL_NAMESPACE::true_type {};
|
105 |
+
|
106 |
+
template <typename TyGroup>
|
107 |
+
using redux_group_optimized = _redux_group_optimized<details::remove_qual<TyGroup>>;
|
108 |
+
|
109 |
+
template <template <class> class TyOp>
|
110 |
+
_CG_STATIC_QUALIFIER int pick_redux(int mask, int val);
|
111 |
+
template <template <class> class TyOp>
|
112 |
+
_CG_STATIC_QUALIFIER unsigned int pick_redux(int mask, unsigned int val);
|
113 |
+
|
114 |
+
#ifdef _CG_HAS_OP_REDUX
|
115 |
+
template <> _CG_QUALIFIER int pick_redux<cooperative_groups::plus>(int mask, int val) {
|
116 |
+
return __reduce_add_sync(mask, val);
|
117 |
+
}
|
118 |
+
template <> _CG_QUALIFIER int pick_redux<cooperative_groups::less>(int mask, int val) {
|
119 |
+
return __reduce_min_sync(mask, val);
|
120 |
+
}
|
121 |
+
template <> _CG_QUALIFIER int pick_redux<cooperative_groups::greater>(int mask, int val) {
|
122 |
+
return __reduce_max_sync(mask, val);
|
123 |
+
}
|
124 |
+
template <> _CG_QUALIFIER int pick_redux<cooperative_groups::bit_and>(int mask, int val) {
|
125 |
+
return __reduce_and_sync(mask, val);
|
126 |
+
}
|
127 |
+
template <> _CG_QUALIFIER int pick_redux<cooperative_groups::bit_xor>(int mask, int val) {
|
128 |
+
return __reduce_xor_sync(mask, val);
|
129 |
+
}
|
130 |
+
template <> _CG_QUALIFIER int pick_redux<cooperative_groups::bit_or>(int mask, int val) {
|
131 |
+
return __reduce_or_sync(mask, val);
|
132 |
+
}
|
133 |
+
|
134 |
+
template <> _CG_QUALIFIER unsigned int pick_redux<cooperative_groups::plus>(int mask, unsigned int val) {
|
135 |
+
return __reduce_add_sync(mask, val);
|
136 |
+
}
|
137 |
+
template <> _CG_QUALIFIER unsigned int pick_redux<cooperative_groups::less>(int mask, unsigned int val) {
|
138 |
+
return __reduce_min_sync(mask, val);
|
139 |
+
}
|
140 |
+
template <> _CG_QUALIFIER unsigned int pick_redux<cooperative_groups::greater>(int mask, unsigned int val) {
|
141 |
+
return __reduce_max_sync(mask, val);
|
142 |
+
}
|
143 |
+
template <> _CG_QUALIFIER unsigned int pick_redux<cooperative_groups::bit_and>(int mask, unsigned int val) {
|
144 |
+
return __reduce_and_sync(mask, val);
|
145 |
+
}
|
146 |
+
template <> _CG_QUALIFIER unsigned int pick_redux<cooperative_groups::bit_xor>(int mask, unsigned int val) {
|
147 |
+
return __reduce_xor_sync(mask, val);
|
148 |
+
}
|
149 |
+
template <> _CG_QUALIFIER unsigned int pick_redux<cooperative_groups::bit_or>(int mask, unsigned int val) {
|
150 |
+
return __reduce_or_sync(mask, val);
|
151 |
+
}
|
152 |
+
#endif
|
153 |
+
|
154 |
+
|
155 |
+
template <typename TyVal, bool = _CG_STL_NAMESPACE::is_unsigned<TyVal>::value>
|
156 |
+
struct _accelerated_op;
|
157 |
+
|
158 |
+
// Signed type redux intrinsic dispatch
|
159 |
+
template <typename TyVal>
|
160 |
+
struct _accelerated_op<TyVal, false> {
|
161 |
+
template <template <class> class TyOp>
|
162 |
+
_CG_STATIC_QUALIFIER TyVal redux(int mask, TyVal val) {
|
163 |
+
return static_cast<TyVal>(pick_redux<TyOp>(mask, static_cast<int>(val)));
|
164 |
+
}
|
165 |
+
};
|
166 |
+
|
167 |
+
// Unsigned type redux intrinsic dispatch
|
168 |
+
template <typename TyVal>
|
169 |
+
struct _accelerated_op<TyVal, true> {
|
170 |
+
template <template <class> class TyOp>
|
171 |
+
_CG_STATIC_QUALIFIER TyVal redux(int mask, TyVal val) {
|
172 |
+
return static_cast<TyVal>(pick_redux<TyOp>(mask, static_cast<unsigned int>(val)));
|
173 |
+
}
|
174 |
+
};
|
175 |
+
|
176 |
+
template <typename TyVal>
|
177 |
+
using accelerated_op = _accelerated_op<TyVal>;
|
178 |
+
|
179 |
+
|
180 |
+
template <typename TyVal, typename TyFnInput, typename TyGroup>
|
181 |
+
class _redux_dispatch {
|
182 |
+
template <class Ty, template <class> class TyOp>
|
183 |
+
using _redux_is_usable = _CG_STL_NAMESPACE::integral_constant<bool,
|
184 |
+
redux_op_supported<Ty, TyOp>::value &&
|
185 |
+
redux_group_optimized<TyGroup>::value>;
|
186 |
+
|
187 |
+
template <class Ty, template <class> class TyOp>
|
188 |
+
using redux_is_usable = typename _CG_STL_NAMESPACE::enable_if<_redux_is_usable<Ty, TyOp>::value, void>::type*;
|
189 |
+
|
190 |
+
template <class Ty, template <class> class TyOp>
|
191 |
+
using redux_is_not_usable = typename _CG_STL_NAMESPACE::enable_if<!_redux_is_usable<Ty, TyOp>::value, void>::type*;
|
192 |
+
|
193 |
+
public:
|
194 |
+
// Dispatch to redux if the combination of op and args are supported
|
195 |
+
template<
|
196 |
+
template <class> class TyOp,
|
197 |
+
redux_is_usable<TyFnInput, TyOp> = nullptr>
|
198 |
+
_CG_STATIC_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyOp<TyFnInput>&& op) -> decltype(op(val, val)) {
|
199 |
+
// Retrieve the mask for the group and dispatch to redux
|
200 |
+
return accelerated_op<TyFnInput>::template redux<TyOp>(_coalesced_group_data_access::get_mask(group), _CG_STL_NAMESPACE::forward<TyVal>(val));
|
201 |
+
}
|
202 |
+
|
203 |
+
template<
|
204 |
+
template <class> class TyOp,
|
205 |
+
redux_is_usable<TyFnInput, TyOp> = nullptr>
|
206 |
+
_CG_STATIC_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyOp<TyFnInput>& op) -> decltype(op(val, val)) {
|
207 |
+
// Retrieve the mask for the group and dispatch to redux
|
208 |
+
return accelerated_op<TyFnInput>::template redux<TyOp>(_coalesced_group_data_access::get_mask(group), _CG_STL_NAMESPACE::forward<TyVal>(val));
|
209 |
+
}
|
210 |
+
|
211 |
+
// Fallback shuffle sync reduction
|
212 |
+
template <
|
213 |
+
template <class> class TyOp,
|
214 |
+
redux_is_not_usable<TyFnInput, TyOp> = nullptr>
|
215 |
+
_CG_STATIC_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyOp<TyFnInput>&& op) -> decltype(op(val, val)) {
|
216 |
+
//Dispatch to fallback shuffle sync accelerated reduction
|
217 |
+
return coalesced_reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp<TyFnInput>>(op));
|
218 |
+
}
|
219 |
+
|
220 |
+
};
|
221 |
+
|
222 |
+
// Group support for reduce.
|
223 |
+
template <class TyGroup> struct _reduce_group_supported : public _CG_STL_NAMESPACE::false_type {};
|
224 |
+
|
225 |
+
template <unsigned int Sz, typename TyPar>
|
226 |
+
struct _reduce_group_supported<cooperative_groups::thread_block_tile<Sz, TyPar>> : public _CG_STL_NAMESPACE::true_type {};
|
227 |
+
template <unsigned int Sz, typename TyPar>
|
228 |
+
struct _reduce_group_supported<internal_thread_block_tile<Sz, TyPar>> : public _CG_STL_NAMESPACE::true_type {};
|
229 |
+
template <>
|
230 |
+
struct _reduce_group_supported<cooperative_groups::coalesced_group> : public _CG_STL_NAMESPACE::true_type {};
|
231 |
+
|
232 |
+
template <typename TyGroup>
|
233 |
+
using reduce_group_supported = _reduce_group_supported<details::remove_qual<TyGroup>>;
|
234 |
+
|
235 |
+
template <typename TyVal, typename TyFnInput, template <class> class TyOp, typename TyGroup>
|
236 |
+
_CG_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyOp<TyFnInput>&& op) -> decltype(op(val, val)) {
|
237 |
+
static_assert(details::is_op_type_same<TyFnInput, TyVal>::value, "Operator and argument types differ");
|
238 |
+
|
239 |
+
using dispatch = details::_redux_dispatch<TyVal, TyFnInput, TyGroup>;
|
240 |
+
return dispatch::reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp<TyFnInput>>(op));
|
241 |
+
}
|
242 |
+
|
243 |
+
template <typename TyVal, typename TyFnInput, template <class> class TyOp, typename TyGroup>
|
244 |
+
_CG_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyOp<TyFnInput>& op) -> decltype(op(val, val)) {
|
245 |
+
static_assert(details::is_op_type_same<TyFnInput, TyVal>::value, "Operator and argument types differ");
|
246 |
+
|
247 |
+
using dispatch = details::_redux_dispatch<TyVal, TyFnInput, TyGroup>;
|
248 |
+
return dispatch::reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp<TyFnInput>>(op));
|
249 |
+
}
|
250 |
+
|
251 |
+
|
252 |
+
template <typename TyVal, typename TyOp, typename TyGroup>
|
253 |
+
_CG_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyOp&& op) -> decltype(op(val, val)) {
|
254 |
+
return details::coalesced_reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyOp>(op));
|
255 |
+
}
|
256 |
+
|
257 |
+
template <unsigned int GroupId>
|
258 |
+
struct tile_reduce_dispatch;
|
259 |
+
|
260 |
+
template <>
|
261 |
+
struct tile_reduce_dispatch<details::coalesced_group_id> {
|
262 |
+
template <typename TyGroup, typename TyVal, typename TyFn>
|
263 |
+
_CG_STATIC_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
264 |
+
return details::reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
265 |
+
}
|
266 |
+
};
|
267 |
+
|
268 |
+
#if defined(_CG_CPP11_FEATURES)
|
269 |
+
template <>
|
270 |
+
struct tile_reduce_dispatch<details::multi_tile_group_id> {
|
271 |
+
template <unsigned int Size, typename ParentT, typename TyVal, typename TyFn>
|
272 |
+
_CG_STATIC_QUALIFIER auto reduce(const thread_block_tile<Size, ParentT>& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
273 |
+
using warpType = details::internal_thread_block_tile<32, __static_size_multi_warp_tile_base<Size>>;
|
274 |
+
using TyRet = details::remove_qual<TyVal>;
|
275 |
+
const unsigned int num_warps = Size / 32;
|
276 |
+
|
277 |
+
auto warp_lambda = [&] (const warpType& warp, TyRet* warp_scratch_location) {
|
278 |
+
*warp_scratch_location =
|
279 |
+
details::reduce(warp, _CG_STL_NAMESPACE::forward<TyVal>(val), op);
|
280 |
+
};
|
281 |
+
auto inter_warp_lambda =
|
282 |
+
[&] (const details::internal_thread_block_tile<num_warps, warpType>& subwarp, TyRet* thread_scratch_location) {
|
283 |
+
*thread_scratch_location =
|
284 |
+
details::reduce(subwarp, *thread_scratch_location, _CG_STL_NAMESPACE::forward<TyFn>(op));
|
285 |
+
};
|
286 |
+
return details::multi_warp_collectives_helper<TyRet>(group, warp_lambda, inter_warp_lambda);
|
287 |
+
}
|
288 |
+
};
|
289 |
+
|
290 |
+
template <unsigned int GroupId>
|
291 |
+
struct tile_async_reduce_dispatch;
|
292 |
+
|
293 |
+
template <>
|
294 |
+
struct tile_async_reduce_dispatch<details::coalesced_group_id> {
|
295 |
+
template <unsigned int TySize, typename ParentT, typename TyDst, typename TyVal, typename TyFn, typename TyResHandler>
|
296 |
+
_CG_STATIC_QUALIFIER void reduce(const __single_warp_thread_block_tile<TySize, ParentT>& group, TyDst& dst, TyVal&& val, TyFn&& op, TyResHandler& res_handler) {
|
297 |
+
// Do regular, in group reduction
|
298 |
+
auto result = details::reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), op);
|
299 |
+
|
300 |
+
// One thread stores/updates the destination
|
301 |
+
if (group.thread_rank() == 0) {
|
302 |
+
res_handler(result);
|
303 |
+
}
|
304 |
+
}
|
305 |
+
template <typename TyDst, typename TyVal, typename TyFn, typename TyResHandler>
|
306 |
+
_CG_STATIC_QUALIFIER void reduce(const coalesced_group& group, TyDst& dst, TyVal&& val, TyFn&& op, TyResHandler& res_handler) {
|
307 |
+
// Do in group reduction to the last thread
|
308 |
+
auto result = details::coalesced_reduce_to_one(group, _CG_STL_NAMESPACE::forward<TyVal>(val), op);
|
309 |
+
|
310 |
+
// One thread stores/updates the destination
|
311 |
+
if (group.thread_rank() == group.size() - 1) {
|
312 |
+
res_handler(result);
|
313 |
+
}
|
314 |
+
}
|
315 |
+
};
|
316 |
+
|
317 |
+
template <>
|
318 |
+
struct tile_async_reduce_dispatch<details::multi_tile_group_id> {
|
319 |
+
template <unsigned int TySize, typename ParentT, typename TyDst, typename TyInputVal, typename TyFn, typename TyResHandler>
|
320 |
+
_CG_STATIC_QUALIFIER void reduce(const thread_block_tile<TySize, ParentT>& group, TyDst& dst, TyInputVal&& val, TyFn&& op, TyResHandler& res_handler) {
|
321 |
+
using TyVal = remove_qual<TyInputVal>;
|
322 |
+
const unsigned int num_warps = TySize / 32;
|
323 |
+
details::barrier_t* sync_location = multi_warp_sync_location_getter(group);
|
324 |
+
auto warp_scratch_location = multi_warp_scratch_location_getter<TyVal>(group, group.thread_rank() / 32);
|
325 |
+
|
326 |
+
// Do in warp reduce
|
327 |
+
auto warp = details::tiled_partition_internal<32, thread_block_tile<TySize, ParentT>>();
|
328 |
+
*warp_scratch_location = details::reduce(warp, _CG_STL_NAMESPACE::forward<TyInputVal>(val), op);
|
329 |
+
|
330 |
+
// Tile of size num_warps from the last warp to arrive does final reduction step
|
331 |
+
if (details::sync_warps_last_releases(sync_location, details::cta::thread_rank(), num_warps)) {
|
332 |
+
auto subwarp = details::tiled_partition_internal<num_warps, decltype(warp)>();
|
333 |
+
if (subwarp.meta_group_rank() == 0) {
|
334 |
+
auto thread_scratch_location = multi_warp_scratch_location_getter<TyVal>(group, subwarp.thread_rank());
|
335 |
+
auto thread_val = *thread_scratch_location;
|
336 |
+
// Release other warps, we read their contribution already.
|
337 |
+
subwarp.sync();
|
338 |
+
details::sync_warps_release(sync_location, subwarp.thread_rank() == 0, details::cta::thread_rank(), num_warps);
|
339 |
+
TyVal result = details::reduce(subwarp, thread_val, op);
|
340 |
+
// One thread stores the result or updates the atomic
|
341 |
+
if (subwarp.thread_rank() == 0) {
|
342 |
+
res_handler(result);
|
343 |
+
}
|
344 |
+
}
|
345 |
+
warp.sync();
|
346 |
+
}
|
347 |
+
}
|
348 |
+
};
|
349 |
+
#endif
|
350 |
+
|
351 |
+
template <typename TyGroup, typename TyInputVal, typename TyRetVal>
|
352 |
+
_CG_QUALIFIER void check_reduce_params() {
|
353 |
+
static_assert(details::is_op_type_same<TyInputVal, TyRetVal>::value, "Operator input and output types differ");
|
354 |
+
static_assert(details::reduce_group_supported<TyGroup>::value, "This group does not exclusively represent a tile");
|
355 |
+
};
|
356 |
+
|
357 |
+
template <typename TyGroup, typename TyDstVal, typename TyInputVal, typename TyRetVal>
|
358 |
+
_CG_QUALIFIER void check_async_reduce_params() {
|
359 |
+
check_reduce_params<TyGroup, TyInputVal, TyRetVal>();
|
360 |
+
static_assert(details::is_op_type_same<TyDstVal, TyInputVal>::value, "Destination and input types differ");
|
361 |
+
}
|
362 |
+
} // details
|
363 |
+
|
364 |
+
template <typename TyGroup, typename TyVal, typename TyFn>
|
365 |
+
_CG_QUALIFIER auto reduce(const TyGroup& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
366 |
+
details::check_reduce_params<TyGroup, details::remove_qual<TyVal>, decltype(op(val, val))>();
|
367 |
+
|
368 |
+
using dispatch = details::tile_reduce_dispatch<TyGroup::_group_id>;
|
369 |
+
return dispatch::reduce(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
370 |
+
}
|
371 |
+
|
372 |
+
#if defined(_CG_CPP11_FEATURES)
|
373 |
+
|
374 |
+
# if defined(_CG_HAS_STL_ATOMICS)
|
375 |
+
template<typename TyGroup, typename TyVal, cuda::thread_scope Sco, typename TyInputVal, typename TyFn>
|
376 |
+
void _CG_QUALIFIER reduce_update_async(const TyGroup& group, cuda::atomic<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) {
|
377 |
+
details::check_async_reduce_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
378 |
+
auto update_lambda = [&] (TyVal& result) {
|
379 |
+
details::atomic_update(dst, result, op);
|
380 |
+
};
|
381 |
+
using dispatch = details::tile_async_reduce_dispatch<TyGroup::_group_id>;
|
382 |
+
dispatch::reduce(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op), update_lambda);
|
383 |
+
}
|
384 |
+
|
385 |
+
template<typename TyGroup, typename TyVal, cuda::thread_scope Sco, typename TyInputVal, typename TyFn>
|
386 |
+
void _CG_QUALIFIER reduce_update_async(const TyGroup& group, const cuda::atomic_ref<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) {
|
387 |
+
details::check_async_reduce_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
388 |
+
auto update_lambda = [&] (TyVal& result) {
|
389 |
+
details::atomic_update(dst, result, op);
|
390 |
+
};
|
391 |
+
using dispatch = details::tile_async_reduce_dispatch<TyGroup::_group_id>;
|
392 |
+
dispatch::reduce(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op), update_lambda);
|
393 |
+
}
|
394 |
+
|
395 |
+
template<typename TyGroup, typename TyVal, cuda::thread_scope Sco, typename TyInputVal, typename TyFn>
|
396 |
+
void _CG_QUALIFIER reduce_store_async(const TyGroup& group, cuda::atomic<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) {
|
397 |
+
details::check_async_reduce_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
398 |
+
auto store_lambda = [&] (TyVal& result) {
|
399 |
+
details::atomic_store(dst, result);
|
400 |
+
};
|
401 |
+
using dispatch = details::tile_async_reduce_dispatch<TyGroup::_group_id>;
|
402 |
+
dispatch::reduce(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op), store_lambda);
|
403 |
+
}
|
404 |
+
|
405 |
+
template<typename TyGroup, typename TyVal, cuda::thread_scope Sco, typename TyInputVal, typename TyFn>
|
406 |
+
void _CG_QUALIFIER reduce_store_async(const TyGroup& group, const cuda::atomic_ref<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) {
|
407 |
+
details::check_async_reduce_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
408 |
+
auto store_lambda = [&] (TyVal& result) {
|
409 |
+
details::atomic_store(dst, result);
|
410 |
+
};
|
411 |
+
using dispatch = details::tile_async_reduce_dispatch<TyGroup::_group_id>;
|
412 |
+
dispatch::reduce(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op), store_lambda);
|
413 |
+
}
|
414 |
+
# endif
|
415 |
+
|
416 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, typename TyFn>
|
417 |
+
void _CG_QUALIFIER reduce_store_async(const TyGroup& group, TyVal* dst, TyInputVal&& val, TyFn&& op) {
|
418 |
+
details::check_async_reduce_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
419 |
+
auto store_lambda = [&] (TyVal& result) {
|
420 |
+
*dst = result;
|
421 |
+
};
|
422 |
+
using dispatch = details::tile_async_reduce_dispatch<TyGroup::_group_id>;
|
423 |
+
dispatch::reduce(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op), store_lambda);
|
424 |
+
}
|
425 |
+
#endif
|
426 |
+
|
427 |
+
_CG_END_NAMESPACE
|
428 |
+
|
429 |
+
#endif // _CG_REDUCE_H_
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/scan.h
ADDED
@@ -0,0 +1,320 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_SCAN_H_
|
50 |
+
#define _CG_SCAN_H_
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
#include "helpers.h"
|
54 |
+
#include "functional.h"
|
55 |
+
#include "coalesced_scan.h"
|
56 |
+
|
57 |
+
_CG_BEGIN_NAMESPACE
|
58 |
+
|
59 |
+
namespace details {
|
60 |
+
|
61 |
+
// Group support for scan.
|
62 |
+
template <class TyGroup> struct _scan_group_supported : public _CG_STL_NAMESPACE::false_type {};
|
63 |
+
|
64 |
+
template <unsigned int Sz, typename TyPar>
|
65 |
+
struct _scan_group_supported<cooperative_groups::thread_block_tile<Sz, TyPar>> : public _CG_STL_NAMESPACE::true_type {};
|
66 |
+
template <unsigned int Sz, typename TyPar>
|
67 |
+
struct _scan_group_supported<internal_thread_block_tile<Sz, TyPar>> : public _CG_STL_NAMESPACE::true_type {};
|
68 |
+
template <>
|
69 |
+
struct _scan_group_supported<cooperative_groups::coalesced_group> : public _CG_STL_NAMESPACE::true_type {};
|
70 |
+
|
71 |
+
template <typename TyGroup>
|
72 |
+
using scan_group_supported = _scan_group_supported<details::remove_qual<TyGroup>>;
|
73 |
+
|
74 |
+
template <bool IsIntegralPlus>
|
75 |
+
struct integral_optimized_scan;
|
76 |
+
|
77 |
+
enum class ScanType { exclusive, inclusive };
|
78 |
+
|
79 |
+
template <unsigned int GroupId, ScanType TyScan>
|
80 |
+
struct scan_dispatch;
|
81 |
+
|
82 |
+
template <ScanType TyScan>
|
83 |
+
struct scan_dispatch<details::coalesced_group_id, TyScan> {
|
84 |
+
template <typename TyGroup, typename TyVal, typename TyFn>
|
85 |
+
_CG_STATIC_QUALIFIER auto scan(const TyGroup& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
86 |
+
auto scan_result = coalesced_inclusive_scan(group, val, op);
|
87 |
+
if (TyScan == ScanType::exclusive) {
|
88 |
+
scan_result = convert_inclusive_to_exclusive(group,
|
89 |
+
scan_result,
|
90 |
+
_CG_STL_NAMESPACE::forward<TyVal>(val),
|
91 |
+
_CG_STL_NAMESPACE::forward<TyFn>(op));
|
92 |
+
}
|
93 |
+
return scan_result;
|
94 |
+
}
|
95 |
+
};
|
96 |
+
|
97 |
+
#if defined(_CG_CPP11_FEATURES)
|
98 |
+
template <ScanType TyScan>
|
99 |
+
struct scan_dispatch<details::multi_tile_group_id, TyScan> {
|
100 |
+
template <unsigned int Size, typename ParentT, typename TyVal, typename TyFn>
|
101 |
+
_CG_STATIC_QUALIFIER auto scan(const thread_block_tile<Size, ParentT>& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
102 |
+
using warpType = details::internal_thread_block_tile<32, __static_size_multi_warp_tile_base<Size>>;
|
103 |
+
using TyRet = details::remove_qual<TyVal>;
|
104 |
+
const unsigned int num_warps = Size / 32;
|
105 |
+
// In warp scan result, calculated in warp_lambda
|
106 |
+
TyRet warp_scan;
|
107 |
+
|
108 |
+
// In warp scan, put sum in the warp_scratch_location
|
109 |
+
auto warp_lambda = [&] (const warpType& warp, TyRet* warp_scratch_location) {
|
110 |
+
warp_scan =
|
111 |
+
details::coalesced_inclusive_scan(warp, _CG_STL_NAMESPACE::forward<TyVal>(val), op);
|
112 |
+
if (warp.thread_rank() + 1 == warp.size()) {
|
113 |
+
*warp_scratch_location = warp_scan;
|
114 |
+
}
|
115 |
+
if (TyScan == ScanType::exclusive) {
|
116 |
+
warp_scan = warp.shfl_up(warp_scan, 1);
|
117 |
+
}
|
118 |
+
};
|
119 |
+
|
120 |
+
// Tile of size num_warps performing the final scan part (exclusive scan of warp sums), other threads will add it
|
121 |
+
// to its in-warp scan result
|
122 |
+
auto inter_warp_lambda =
|
123 |
+
[&] (const details::internal_thread_block_tile<num_warps, warpType>& subwarp, TyRet* thread_scratch_location) {
|
124 |
+
auto thread_val = *thread_scratch_location;
|
125 |
+
auto result = coalesced_inclusive_scan(subwarp, thread_val, op);
|
126 |
+
*thread_scratch_location = convert_inclusive_to_exclusive(subwarp, result, thread_val, op);
|
127 |
+
};
|
128 |
+
|
129 |
+
TyRet previous_warps_sum = details::multi_warp_collectives_helper<TyRet>(group, warp_lambda, inter_warp_lambda);
|
130 |
+
if (TyScan == ScanType::exclusive && warpType::thread_rank() == 0) {
|
131 |
+
return previous_warps_sum;
|
132 |
+
}
|
133 |
+
if (warpType::meta_group_rank() == 0) {
|
134 |
+
return warp_scan;
|
135 |
+
}
|
136 |
+
else {
|
137 |
+
return op(warp_scan, previous_warps_sum);
|
138 |
+
}
|
139 |
+
}
|
140 |
+
};
|
141 |
+
|
142 |
+
#if defined(_CG_HAS_STL_ATOMICS)
|
143 |
+
template <unsigned int GroupId, ScanType TyScan>
|
144 |
+
struct scan_update_dispatch;
|
145 |
+
|
146 |
+
template <ScanType TyScan>
|
147 |
+
struct scan_update_dispatch<details::coalesced_group_id, TyScan> {
|
148 |
+
template <typename TyGroup, typename TyAtomic, typename TyVal, typename TyFn>
|
149 |
+
_CG_STATIC_QUALIFIER auto scan(const TyGroup& group, TyAtomic& dst, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
150 |
+
details::remove_qual<TyVal> old;
|
151 |
+
|
152 |
+
// Do regular in group scan
|
153 |
+
auto scan_result = details::coalesced_inclusive_scan(group, val, op);
|
154 |
+
|
155 |
+
// Last thread updates the atomic and distributes its old value to other threads
|
156 |
+
if (group.thread_rank() == group.size() - 1) {
|
157 |
+
old = atomic_update(dst, scan_result, _CG_STL_NAMESPACE::forward<TyFn>(op));
|
158 |
+
}
|
159 |
+
old = group.shfl(old, group.size() - 1);
|
160 |
+
if (TyScan == ScanType::exclusive) {
|
161 |
+
scan_result = convert_inclusive_to_exclusive(group, scan_result, _CG_STL_NAMESPACE::forward<TyVal>(val), op);
|
162 |
+
}
|
163 |
+
scan_result = op(old, scan_result);
|
164 |
+
return scan_result;
|
165 |
+
}
|
166 |
+
};
|
167 |
+
|
168 |
+
template <ScanType TyScan>
|
169 |
+
struct scan_update_dispatch<details::multi_tile_group_id, TyScan> {
|
170 |
+
template <unsigned int Size, typename ParentT, typename TyAtomic, typename TyVal, typename TyFn>
|
171 |
+
_CG_STATIC_QUALIFIER auto scan(const thread_block_tile<Size, ParentT>& group, TyAtomic& dst, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
172 |
+
using warpType = details::internal_thread_block_tile<32, __static_size_multi_warp_tile_base<Size>>;
|
173 |
+
using TyRet = details::remove_qual<TyVal>;
|
174 |
+
const unsigned int num_warps = Size / 32;
|
175 |
+
// In warp scan result, calculated in warp_lambda
|
176 |
+
TyRet warp_scan;
|
177 |
+
|
178 |
+
// In warp scan, put sum in the warp_scratch_location
|
179 |
+
auto warp_lambda = [&] (const warpType& warp, TyRet* warp_scratch_location) {
|
180 |
+
warp_scan =
|
181 |
+
details::coalesced_inclusive_scan(warp, _CG_STL_NAMESPACE::forward<TyVal>(val), op);
|
182 |
+
if (warp.thread_rank() + 1 == warp.size()) {
|
183 |
+
*warp_scratch_location = warp_scan;
|
184 |
+
}
|
185 |
+
if (TyScan == ScanType::exclusive) {
|
186 |
+
warp_scan = warp.shfl_up(warp_scan, 1);
|
187 |
+
}
|
188 |
+
};
|
189 |
+
|
190 |
+
// Tile of size num_warps performing the final scan part (exclusive scan of warp sums), other threads will add it
|
191 |
+
// to its in-warp scan result
|
192 |
+
auto inter_warp_lambda =
|
193 |
+
[&] (const details::internal_thread_block_tile<num_warps, warpType>& subwarp, TyRet* thread_scratch_location) {
|
194 |
+
auto thread_val = *thread_scratch_location;
|
195 |
+
auto scan_result = details::coalesced_inclusive_scan(subwarp, thread_val, op);
|
196 |
+
TyRet offset;
|
197 |
+
// Single thread does the atomic update with sum of all contributions and reads the old value.
|
198 |
+
if (subwarp.thread_rank() == subwarp.size() - 1) {
|
199 |
+
offset = details::atomic_update(dst, scan_result, op);
|
200 |
+
}
|
201 |
+
offset = subwarp.shfl(offset, subwarp.size() - 1);
|
202 |
+
scan_result = convert_inclusive_to_exclusive(subwarp, scan_result, thread_val, op);
|
203 |
+
// Add offset read from the atomic to the scanned warp sum.
|
204 |
+
// Skipping first thread, since it got defautly constructed value from the conversion,
|
205 |
+
// it should just return the offset received from the thread that did the atomic update.
|
206 |
+
if (subwarp.thread_rank() != 0) {
|
207 |
+
offset = op(scan_result, offset);
|
208 |
+
}
|
209 |
+
*thread_scratch_location = offset;
|
210 |
+
};
|
211 |
+
|
212 |
+
TyRet previous_warps_sum = details::multi_warp_collectives_helper<TyRet>(group, warp_lambda, inter_warp_lambda);
|
213 |
+
if (TyScan == ScanType::exclusive && warpType::thread_rank() == 0) {
|
214 |
+
return previous_warps_sum;
|
215 |
+
}
|
216 |
+
return op(warp_scan, previous_warps_sum);
|
217 |
+
}
|
218 |
+
};
|
219 |
+
#endif
|
220 |
+
#endif
|
221 |
+
|
222 |
+
template <typename TyGroup, typename TyInputVal, typename TyRetVal>
|
223 |
+
_CG_QUALIFIER void check_scan_params() {
|
224 |
+
static_assert(details::is_op_type_same<TyInputVal, TyRetVal>::value, "Operator input and output types differ");
|
225 |
+
static_assert(details::scan_group_supported<TyGroup>::value, "This group does not exclusively represent a tile");
|
226 |
+
}
|
227 |
+
|
228 |
+
#if defined(_CG_HAS_STL_ATOMICS)
|
229 |
+
template <typename TyGroup, typename TyDstVal, typename TyInputVal, typename TyRetVal>
|
230 |
+
_CG_QUALIFIER void check_scan_update_params() {
|
231 |
+
check_scan_params<TyGroup, TyInputVal, TyRetVal>();
|
232 |
+
static_assert(details::is_op_type_same<TyDstVal, TyInputVal>::value, "Destination and input types differ");
|
233 |
+
}
|
234 |
+
#endif
|
235 |
+
|
236 |
+
} // details
|
237 |
+
|
238 |
+
template <typename TyGroup, typename TyVal, typename TyFn>
|
239 |
+
_CG_QUALIFIER auto inclusive_scan(const TyGroup& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
240 |
+
details::check_scan_params<TyGroup, TyVal, decltype(op(val, val))>();
|
241 |
+
|
242 |
+
using dispatch = details::scan_dispatch<TyGroup::_group_id, details::ScanType::inclusive>;
|
243 |
+
return dispatch::scan(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
244 |
+
}
|
245 |
+
|
246 |
+
template <typename TyGroup, typename TyVal>
|
247 |
+
_CG_QUALIFIER details::remove_qual<TyVal> inclusive_scan(const TyGroup& group, TyVal&& val) {
|
248 |
+
return inclusive_scan(group, _CG_STL_NAMESPACE::forward<TyVal>(val), cooperative_groups::plus<details::remove_qual<TyVal>>());
|
249 |
+
}
|
250 |
+
|
251 |
+
template <typename TyGroup, typename TyVal, typename TyFn>
|
252 |
+
_CG_QUALIFIER auto exclusive_scan(const TyGroup& group, TyVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
253 |
+
details::check_scan_params<TyGroup, TyVal, decltype(op(val, val))>();
|
254 |
+
|
255 |
+
using dispatch = details::scan_dispatch<TyGroup::_group_id, details::ScanType::exclusive>;
|
256 |
+
return dispatch::scan(group, _CG_STL_NAMESPACE::forward<TyVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
257 |
+
}
|
258 |
+
|
259 |
+
template <typename TyGroup, typename TyVal>
|
260 |
+
_CG_QUALIFIER details::remove_qual<TyVal> exclusive_scan(const TyGroup& group, TyVal&& val) {
|
261 |
+
return exclusive_scan(group, _CG_STL_NAMESPACE::forward<TyVal>(val), cooperative_groups::plus<details::remove_qual<TyVal>>());
|
262 |
+
}
|
263 |
+
|
264 |
+
#if defined(_CG_HAS_STL_ATOMICS)
|
265 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco, typename TyFn>
|
266 |
+
_CG_QUALIFIER auto inclusive_scan_update(const TyGroup& group, cuda::atomic<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
267 |
+
details::check_scan_update_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
268 |
+
|
269 |
+
using dispatch = details::scan_update_dispatch<TyGroup::_group_id, details::ScanType::inclusive>;
|
270 |
+
return dispatch::scan(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
271 |
+
}
|
272 |
+
|
273 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco>
|
274 |
+
_CG_QUALIFIER TyVal inclusive_scan_update(const TyGroup& group, cuda::atomic<TyVal, Sco> & dst, TyInputVal&& val) {
|
275 |
+
return inclusive_scan_update(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), cooperative_groups::plus<TyVal>());
|
276 |
+
}
|
277 |
+
|
278 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco, typename TyFn>
|
279 |
+
_CG_QUALIFIER auto exclusive_scan_update(const TyGroup& group, cuda::atomic<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
280 |
+
details::check_scan_update_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
281 |
+
|
282 |
+
using dispatch = details::scan_update_dispatch<TyGroup::_group_id, details::ScanType::exclusive>;
|
283 |
+
return dispatch::scan(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
284 |
+
}
|
285 |
+
|
286 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco>
|
287 |
+
_CG_QUALIFIER TyVal exclusive_scan_update(const TyGroup& group, cuda::atomic<TyVal, Sco>& dst, TyInputVal&& val) {
|
288 |
+
return exclusive_scan_update(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), cooperative_groups::plus<TyVal>());
|
289 |
+
}
|
290 |
+
|
291 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco, typename TyFn>
|
292 |
+
_CG_QUALIFIER auto inclusive_scan_update(const TyGroup& group, const cuda::atomic_ref<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
293 |
+
details::check_scan_update_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
294 |
+
|
295 |
+
using dispatch = details::scan_update_dispatch<TyGroup::_group_id, details::ScanType::inclusive>;
|
296 |
+
return dispatch::scan(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
297 |
+
}
|
298 |
+
|
299 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco>
|
300 |
+
_CG_QUALIFIER TyVal inclusive_scan_update(const TyGroup& group, const cuda::atomic_ref<TyVal, Sco> & dst, TyInputVal&& val) {
|
301 |
+
return inclusive_scan_update(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), cooperative_groups::plus<TyVal>());
|
302 |
+
}
|
303 |
+
|
304 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco, typename TyFn>
|
305 |
+
_CG_QUALIFIER auto exclusive_scan_update(const TyGroup& group, const cuda::atomic_ref<TyVal, Sco>& dst, TyInputVal&& val, TyFn&& op) -> decltype(op(val, val)) {
|
306 |
+
details::check_scan_update_params<TyGroup, TyVal, details::remove_qual<TyInputVal>, decltype(op(val, val))>();
|
307 |
+
|
308 |
+
using dispatch = details::scan_update_dispatch<TyGroup::_group_id, details::ScanType::exclusive>;
|
309 |
+
return dispatch::scan(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), _CG_STL_NAMESPACE::forward<TyFn>(op));
|
310 |
+
}
|
311 |
+
|
312 |
+
template<typename TyGroup, typename TyVal, typename TyInputVal, cuda::thread_scope Sco>
|
313 |
+
_CG_QUALIFIER TyVal exclusive_scan_update(const TyGroup& group, const cuda::atomic_ref<TyVal, Sco>& dst, TyInputVal&& val) {
|
314 |
+
return exclusive_scan_update(group, dst, _CG_STL_NAMESPACE::forward<TyInputVal>(val), cooperative_groups::plus<TyVal>());
|
315 |
+
}
|
316 |
+
#endif
|
317 |
+
|
318 |
+
_CG_END_NAMESPACE
|
319 |
+
|
320 |
+
#endif // _CG_SCAN_H_
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/details/sync.h
ADDED
@@ -0,0 +1,267 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _CG_GRID_H
|
50 |
+
#define _CG_GRID_H
|
51 |
+
|
52 |
+
#include "info.h"
|
53 |
+
|
54 |
+
_CG_BEGIN_NAMESPACE
|
55 |
+
|
56 |
+
namespace details
|
57 |
+
{
|
58 |
+
|
59 |
+
typedef unsigned int barrier_t;
|
60 |
+
|
61 |
+
_CG_STATIC_QUALIFIER bool bar_has_flipped(unsigned int old_arrive, unsigned int current_arrive) {
|
62 |
+
return (((old_arrive ^ current_arrive) & 0x80000000) != 0);
|
63 |
+
}
|
64 |
+
|
65 |
+
_CG_STATIC_QUALIFIER void sync_grids(unsigned int expected, volatile barrier_t *arrived) {
|
66 |
+
bool cta_master = (threadIdx.x + threadIdx.y + threadIdx.z == 0);
|
67 |
+
bool gpu_master = (blockIdx.x + blockIdx.y + blockIdx.z == 0);
|
68 |
+
|
69 |
+
__barrier_sync(0);
|
70 |
+
|
71 |
+
if (cta_master) {
|
72 |
+
unsigned int oldArrive;
|
73 |
+
unsigned int nb = 1;
|
74 |
+
if (gpu_master) {
|
75 |
+
nb = 0x80000000 - (expected - 1);
|
76 |
+
}
|
77 |
+
|
78 |
+
#if __CUDA_ARCH__ < 700
|
79 |
+
// Fence; barrier update; volatile polling; fence
|
80 |
+
__threadfence();
|
81 |
+
|
82 |
+
oldArrive = atomicAdd((unsigned int*)arrived, nb);
|
83 |
+
|
84 |
+
while (!bar_has_flipped(oldArrive, *arrived));
|
85 |
+
|
86 |
+
__threadfence();
|
87 |
+
#else
|
88 |
+
// Barrier update with release; polling with acquire
|
89 |
+
asm volatile("atom.add.release.gpu.u32 %0,[%1],%2;" : "=r"(oldArrive) : _CG_ASM_PTR_CONSTRAINT((unsigned int*)arrived), "r"(nb) : "memory");
|
90 |
+
|
91 |
+
unsigned int current_arrive;
|
92 |
+
do {
|
93 |
+
asm volatile("ld.acquire.gpu.u32 %0,[%1];" : "=r"(current_arrive) : _CG_ASM_PTR_CONSTRAINT((unsigned int *)arrived) : "memory");
|
94 |
+
} while (!bar_has_flipped(oldArrive, current_arrive));
|
95 |
+
#endif
|
96 |
+
}
|
97 |
+
|
98 |
+
__barrier_sync(0);
|
99 |
+
}
|
100 |
+
|
101 |
+
/* - Multi warp groups synchronization routines - */
|
102 |
+
|
103 |
+
// Need both acquire and release for the last warp, since it won't be able to acquire with red.and
|
104 |
+
_CG_STATIC_QUALIFIER unsigned int atom_or_acq_rel_cta(unsigned int *addr, unsigned int val) {
|
105 |
+
unsigned int old;
|
106 |
+
#if __CUDA_ARCH__ < 700
|
107 |
+
__threadfence_block();
|
108 |
+
old = atomicOr(addr, val);
|
109 |
+
#else
|
110 |
+
asm volatile("atom.or.acq_rel.cta.b32 %0,[%1],%2;" : "=r"(old) : _CG_ASM_PTR_CONSTRAINT(addr), "r"(val) : "memory");
|
111 |
+
#endif
|
112 |
+
return old;
|
113 |
+
}
|
114 |
+
|
115 |
+
// Special case where barrier is arrived, but not waited on
|
116 |
+
_CG_STATIC_QUALIFIER void red_or_release_cta(unsigned int *addr, unsigned int val) {
|
117 |
+
#if __CUDA_ARCH__ < 700
|
118 |
+
__threadfence_block();
|
119 |
+
atomicOr(addr, val);
|
120 |
+
#else
|
121 |
+
asm volatile("red.or.release.cta.b32 [%0],%1;" :: _CG_ASM_PTR_CONSTRAINT(addr), "r"(val) : "memory");
|
122 |
+
#endif
|
123 |
+
}
|
124 |
+
|
125 |
+
// Usually called by last arriving warp to released other warps, can be relaxed, since or was already acq_rel
|
126 |
+
_CG_STATIC_QUALIFIER void red_and_relaxed_cta(unsigned int *addr, unsigned int val) {
|
127 |
+
#if __CUDA_ARCH__ < 700
|
128 |
+
atomicAnd(addr, val);
|
129 |
+
#else
|
130 |
+
asm volatile("red.and.relaxed.cta.b32 [%0],%1;" :: _CG_ASM_PTR_CONSTRAINT(addr), "r"(val) : "memory");
|
131 |
+
#endif
|
132 |
+
}
|
133 |
+
|
134 |
+
// Special case of release, where last warp was doing extra work before releasing others, need to be release
|
135 |
+
// to ensure that extra work is visible
|
136 |
+
_CG_STATIC_QUALIFIER void red_and_release_cta(unsigned int *addr, unsigned int val) {
|
137 |
+
#if __CUDA_ARCH__ < 700
|
138 |
+
__threadfence_block();
|
139 |
+
atomicAnd(addr, val);
|
140 |
+
#else
|
141 |
+
asm volatile("red.and.release.cta.b32 [%0],%1;" :: _CG_ASM_PTR_CONSTRAINT(addr), "r"(val) : "memory");
|
142 |
+
#endif
|
143 |
+
}
|
144 |
+
|
145 |
+
// Read the barrier, acquire to ensure all memory operations following the sync are correctly performed after it is released
|
146 |
+
_CG_STATIC_QUALIFIER unsigned int ld_acquire_cta(unsigned int *addr) {
|
147 |
+
unsigned int val;
|
148 |
+
#if __CUDA_ARCH__ < 700
|
149 |
+
val = *((volatile unsigned int*) addr);
|
150 |
+
__threadfence_block();
|
151 |
+
#else
|
152 |
+
asm volatile("ld.acquire.cta.u32 %0,[%1];" : "=r"(val) : _CG_ASM_PTR_CONSTRAINT(addr) : "memory");
|
153 |
+
#endif
|
154 |
+
return val;
|
155 |
+
}
|
156 |
+
|
157 |
+
// Get synchronization bit mask of my thread_block_tile of size num_warps. Thread ranks 0..31 have the first bit assigned to them,
|
158 |
+
// thread ranks 32..63 second etc
|
159 |
+
// Bit masks are unique for each group, groups of the same size will have the same number of bits set, but on different positions
|
160 |
+
_CG_STATIC_QUALIFIER unsigned int get_group_mask(unsigned int thread_rank, unsigned int num_warps) {
|
161 |
+
return num_warps == 32 ? ~0 : ((1 << num_warps) - 1) << (num_warps * (thread_rank / (num_warps * 32)));
|
162 |
+
}
|
163 |
+
|
164 |
+
_CG_STATIC_QUALIFIER void barrier_wait(barrier_t *arrived, unsigned int warp_bit) {
|
165 |
+
while(ld_acquire_cta(arrived) & warp_bit);
|
166 |
+
}
|
167 |
+
|
168 |
+
// Default blocking sync.
|
169 |
+
_CG_STATIC_QUALIFIER void sync_warps(barrier_t *arrived, unsigned int thread_rank, unsigned int num_warps) {
|
170 |
+
unsigned int warp_id = thread_rank / 32;
|
171 |
+
bool warp_master = (thread_rank % 32 == 0);
|
172 |
+
unsigned int warp_bit = 1 << warp_id;
|
173 |
+
unsigned int group_mask = get_group_mask(thread_rank, num_warps);
|
174 |
+
|
175 |
+
__syncwarp(0xFFFFFFFF);
|
176 |
+
|
177 |
+
if (warp_master) {
|
178 |
+
unsigned int old = atom_or_acq_rel_cta(arrived, warp_bit);
|
179 |
+
if (((old | warp_bit) & group_mask) == group_mask) {
|
180 |
+
red_and_relaxed_cta(arrived, ~group_mask);
|
181 |
+
}
|
182 |
+
else {
|
183 |
+
barrier_wait(arrived, warp_bit);
|
184 |
+
}
|
185 |
+
}
|
186 |
+
|
187 |
+
__syncwarp(0xFFFFFFFF);
|
188 |
+
}
|
189 |
+
|
190 |
+
// Blocking sync, except the last arriving warp, that releases other warps, returns to do other stuff first.
|
191 |
+
// Warp returning true from this function needs to call sync_warps_release.
|
192 |
+
_CG_STATIC_QUALIFIER bool sync_warps_last_releases(barrier_t *arrived, unsigned int thread_rank, unsigned int num_warps) {
|
193 |
+
unsigned int warp_id = thread_rank / 32;
|
194 |
+
bool warp_master = (thread_rank % 32 == 0);
|
195 |
+
unsigned int warp_bit = 1 << warp_id;
|
196 |
+
unsigned int group_mask = get_group_mask(thread_rank, num_warps);
|
197 |
+
|
198 |
+
__syncwarp(0xFFFFFFFF);
|
199 |
+
|
200 |
+
unsigned int old = 0;
|
201 |
+
if (warp_master) {
|
202 |
+
old = atom_or_acq_rel_cta(arrived, warp_bit);
|
203 |
+
}
|
204 |
+
old = __shfl_sync(0xFFFFFFFF, old, 0);
|
205 |
+
if (((old | warp_bit) & group_mask) == group_mask) {
|
206 |
+
return true;
|
207 |
+
}
|
208 |
+
barrier_wait(arrived, warp_bit);
|
209 |
+
|
210 |
+
return false;
|
211 |
+
}
|
212 |
+
|
213 |
+
// Release my group from the barrier.
|
214 |
+
_CG_STATIC_QUALIFIER void sync_warps_release(barrier_t *arrived, bool is_master, unsigned int thread_rank, unsigned int num_warps) {
|
215 |
+
unsigned int group_mask = get_group_mask(thread_rank, num_warps);
|
216 |
+
if (is_master) {
|
217 |
+
red_and_release_cta(arrived, ~group_mask);
|
218 |
+
}
|
219 |
+
}
|
220 |
+
|
221 |
+
// Arrive at my group barrier, but don't block or release the barrier, even if every one arrives.
|
222 |
+
// sync_warps_release needs to be called by some warp after this one to reset the barrier.
|
223 |
+
_CG_STATIC_QUALIFIER void sync_warps_arrive(barrier_t *arrived, unsigned int thread_rank, unsigned int num_warps) {
|
224 |
+
unsigned int warp_id = thread_rank / 32;
|
225 |
+
bool warp_master = (thread_rank % 32 == 0);
|
226 |
+
unsigned int warp_bit = 1 << warp_id;
|
227 |
+
unsigned int group_mask = get_group_mask(thread_rank, num_warps);
|
228 |
+
|
229 |
+
__syncwarp(0xFFFFFFFF);
|
230 |
+
|
231 |
+
if (warp_master) {
|
232 |
+
red_or_release_cta(arrived, warp_bit);
|
233 |
+
}
|
234 |
+
}
|
235 |
+
|
236 |
+
// Wait for my warp to be released from the barrier. Warp must have arrived first.
|
237 |
+
_CG_STATIC_QUALIFIER void sync_warps_wait(barrier_t *arrived, unsigned int thread_rank) {
|
238 |
+
unsigned int warp_id = thread_rank / 32;
|
239 |
+
unsigned int warp_bit = 1 << warp_id;
|
240 |
+
|
241 |
+
barrier_wait(arrived, warp_bit);
|
242 |
+
}
|
243 |
+
|
244 |
+
// Wait for specific warp to arrive at the barrier
|
245 |
+
_CG_QUALIFIER void sync_warps_wait_for_specific_warp(barrier_t *arrived, unsigned int wait_warp_id) {
|
246 |
+
unsigned int wait_mask = 1 << wait_warp_id;
|
247 |
+
while((ld_acquire_cta(arrived) & wait_mask) != wait_mask);
|
248 |
+
}
|
249 |
+
|
250 |
+
// Initialize the bit corresponding to my warp in the barrier
|
251 |
+
_CG_QUALIFIER void sync_warps_reset(barrier_t *arrived, unsigned int thread_rank) {
|
252 |
+
unsigned int warp_id = thread_rank / 32;
|
253 |
+
unsigned int warp_bit = 1 << warp_id;
|
254 |
+
|
255 |
+
__syncwarp(0xFFFFFFFF);
|
256 |
+
|
257 |
+
if (thread_rank % 32 == 0) {
|
258 |
+
red_and_release_cta(arrived, ~warp_bit);
|
259 |
+
}
|
260 |
+
// No need to sync after the atomic, there will be a sync of the group that is being partitioned right after this.
|
261 |
+
}
|
262 |
+
|
263 |
+
} // details
|
264 |
+
|
265 |
+
_CG_END_NAMESPACE
|
266 |
+
|
267 |
+
#endif // _CG_GRID_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/memcpy_async.h
ADDED
@@ -0,0 +1,62 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _COOPERATIVE_GROUPS_MEMCPY_ASYNC
|
50 |
+
#define _COOPERATIVE_GROUPS_MEMCPY_ASYNC
|
51 |
+
|
52 |
+
#include "../cooperative_groups.h"
|
53 |
+
#include "details/info.h"
|
54 |
+
|
55 |
+
#ifdef _CG_CPP11_FEATURES
|
56 |
+
# include "details/async.h"
|
57 |
+
#else
|
58 |
+
# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
|
59 |
+
-std=c++11 compiler option.
|
60 |
+
#endif
|
61 |
+
|
62 |
+
#endif // _COOPERATIVE_GROUPS_MEMCPY_ASYNC
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/reduce.h
ADDED
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _COOPERATIVE_GROUPS_REDUCE_H
|
50 |
+
#define _COOPERATIVE_GROUPS_REDUCE_H
|
51 |
+
|
52 |
+
#include "../cooperative_groups.h"
|
53 |
+
#include "details/info.h"
|
54 |
+
|
55 |
+
#ifdef _CG_CPP11_FEATURES
|
56 |
+
# include "details/reduce.h"
|
57 |
+
#else
|
58 |
+
# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
|
59 |
+
-std=c++11 compiler option.
|
60 |
+
#endif
|
61 |
+
|
62 |
+
|
63 |
+
#endif //_COOPERATIVE_GROUPS_REDUCE_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cooperative_groups/scan.h
ADDED
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
1 |
+
/* Copyright 1993-2016 NVIDIA Corporation. All rights reserved.
|
2 |
+
*
|
3 |
+
* NOTICE TO LICENSEE:
|
4 |
+
*
|
5 |
+
* The source code and/or documentation ("Licensed Deliverables") are
|
6 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
7 |
+
* international Copyright laws.
|
8 |
+
*
|
9 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
10 |
+
* CONFIDENTIAL to NVIDIA and are being provided under the terms and
|
11 |
+
* conditions of a form of NVIDIA software license agreement by and
|
12 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
13 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
14 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
15 |
+
* of the Licensed Deliverables to any third party without the express
|
16 |
+
* written consent of NVIDIA is prohibited.
|
17 |
+
*
|
18 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
19 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
20 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. THEY ARE
|
21 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
22 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
23 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
24 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
25 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
26 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
27 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
28 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
29 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
30 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
31 |
+
* OF THESE LICENSED DELIVERABLES.
|
32 |
+
*
|
33 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
34 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
35 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
36 |
+
* computer software documentation" as such terms are used in 48
|
37 |
+
* C.F.R. 12.212 (SEPT 1995) and are provided to the U.S. Government
|
38 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
39 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
40 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
41 |
+
* only those rights set forth herein.
|
42 |
+
*
|
43 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
44 |
+
* software must include, in the user documentation and internal
|
45 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
46 |
+
* Users Notice.
|
47 |
+
*/
|
48 |
+
|
49 |
+
#ifndef _COOPERATIVE_GROUPS_SCAN_H
|
50 |
+
#define _COOPERATIVE_GROUPS_SCAN_H
|
51 |
+
|
52 |
+
#include "../cooperative_groups.h"
|
53 |
+
#include "details/info.h"
|
54 |
+
|
55 |
+
#ifdef _CG_CPP11_FEATURES
|
56 |
+
# include "details/scan.h"
|
57 |
+
#else
|
58 |
+
# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
|
59 |
+
-std=c++11 compiler option.
|
60 |
+
#endif
|
61 |
+
|
62 |
+
|
63 |
+
#endif //_COOPERATIVE_GROUPS_SCAN_H
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cudaVDPAU.h
ADDED
@@ -0,0 +1,282 @@
|
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|
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|
|
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|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
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|
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|
|
|
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|
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|
|
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|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 2010-2014 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#ifndef CUDAVDPAU_H
|
51 |
+
#define CUDAVDPAU_H
|
52 |
+
|
53 |
+
#ifdef CUDA_FORCE_API_VERSION
|
54 |
+
#error "CUDA_FORCE_API_VERSION is no longer supported."
|
55 |
+
#endif
|
56 |
+
|
57 |
+
#define cuVDPAUCtxCreate cuVDPAUCtxCreate_v2
|
58 |
+
|
59 |
+
#ifdef __cplusplus
|
60 |
+
extern "C" {
|
61 |
+
#endif
|
62 |
+
|
63 |
+
/**
|
64 |
+
* \defgroup CUDA_VDPAU VDPAU Interoperability
|
65 |
+
* \ingroup CUDA_DRIVER
|
66 |
+
*
|
67 |
+
* ___MANBRIEF___ VDPAU interoperability functions of the low-level CUDA driver
|
68 |
+
* API (___CURRENT_FILE___) ___ENDMANBRIEF___
|
69 |
+
*
|
70 |
+
* This section describes the VDPAU interoperability functions of the
|
71 |
+
* low-level CUDA driver application programming interface.
|
72 |
+
*
|
73 |
+
* @{
|
74 |
+
*/
|
75 |
+
|
76 |
+
/**
|
77 |
+
* \brief Gets the CUDA device associated with a VDPAU device
|
78 |
+
*
|
79 |
+
* Returns in \p *pDevice the CUDA device associated with a \p vdpDevice, if
|
80 |
+
* applicable.
|
81 |
+
*
|
82 |
+
* \param pDevice - Device associated with vdpDevice
|
83 |
+
* \param vdpDevice - A VdpDevice handle
|
84 |
+
* \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
|
85 |
+
*
|
86 |
+
* \return
|
87 |
+
* ::CUDA_SUCCESS,
|
88 |
+
* ::CUDA_ERROR_DEINITIALIZED,
|
89 |
+
* ::CUDA_ERROR_NOT_INITIALIZED,
|
90 |
+
* ::CUDA_ERROR_INVALID_CONTEXT,
|
91 |
+
* ::CUDA_ERROR_INVALID_VALUE
|
92 |
+
* \notefnerr
|
93 |
+
*
|
94 |
+
* \sa ::cuCtxCreate, ::cuVDPAUCtxCreate, ::cuGraphicsVDPAURegisterVideoSurface,
|
95 |
+
* ::cuGraphicsVDPAURegisterOutputSurface, ::cuGraphicsUnregisterResource,
|
96 |
+
* ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
|
97 |
+
* ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
|
98 |
+
* ::cudaVDPAUGetDevice
|
99 |
+
*/
|
100 |
+
CUresult CUDAAPI cuVDPAUGetDevice(CUdevice *pDevice, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
|
101 |
+
|
102 |
+
/**
|
103 |
+
* \brief Create a CUDA context for interoperability with VDPAU
|
104 |
+
*
|
105 |
+
* Creates a new CUDA context, initializes VDPAU interoperability, and
|
106 |
+
* associates the CUDA context with the calling thread. It must be called
|
107 |
+
* before performing any other VDPAU interoperability operations. It may fail
|
108 |
+
* if the needed VDPAU driver facilities are not available. For usage of the
|
109 |
+
* \p flags parameter, see ::cuCtxCreate().
|
110 |
+
*
|
111 |
+
* \param pCtx - Returned CUDA context
|
112 |
+
* \param flags - Options for CUDA context creation
|
113 |
+
* \param device - Device on which to create the context
|
114 |
+
* \param vdpDevice - The VdpDevice to interop with
|
115 |
+
* \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
|
116 |
+
*
|
117 |
+
* \return
|
118 |
+
* ::CUDA_SUCCESS,
|
119 |
+
* ::CUDA_ERROR_DEINITIALIZED,
|
120 |
+
* ::CUDA_ERROR_NOT_INITIALIZED,
|
121 |
+
* ::CUDA_ERROR_INVALID_CONTEXT,
|
122 |
+
* ::CUDA_ERROR_INVALID_VALUE,
|
123 |
+
* ::CUDA_ERROR_OUT_OF_MEMORY
|
124 |
+
* \notefnerr
|
125 |
+
*
|
126 |
+
* \sa ::cuCtxCreate, ::cuGraphicsVDPAURegisterVideoSurface,
|
127 |
+
* ::cuGraphicsVDPAURegisterOutputSurface, ::cuGraphicsUnregisterResource,
|
128 |
+
* ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
|
129 |
+
* ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
|
130 |
+
* ::cuVDPAUGetDevice
|
131 |
+
*/
|
132 |
+
CUresult CUDAAPI cuVDPAUCtxCreate(CUcontext *pCtx, unsigned int flags, CUdevice device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
|
133 |
+
|
134 |
+
/**
|
135 |
+
* \brief Registers a VDPAU VdpVideoSurface object
|
136 |
+
*
|
137 |
+
* Registers the VdpVideoSurface specified by \p vdpSurface for access by
|
138 |
+
* CUDA. A handle to the registered object is returned as \p pCudaResource.
|
139 |
+
* The surface's intended usage is specified using \p flags, as follows:
|
140 |
+
*
|
141 |
+
* - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE: Specifies no hints about how this
|
142 |
+
* resource will be used. It is therefore assumed that this resource will be
|
143 |
+
* read from and written to by CUDA. This is the default value.
|
144 |
+
* - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_READ_ONLY: Specifies that CUDA
|
145 |
+
* will not write to this resource.
|
146 |
+
* - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_WRITE_DISCARD: Specifies that
|
147 |
+
* CUDA will not read from this resource and will write over the
|
148 |
+
* entire contents of the resource, so none of the data previously
|
149 |
+
* stored in the resource will be preserved.
|
150 |
+
*
|
151 |
+
* The VdpVideoSurface is presented as an array of subresources that may be
|
152 |
+
* accessed using pointers returned by ::cuGraphicsSubResourceGetMappedArray.
|
153 |
+
* The exact number of valid \p arrayIndex values depends on the VDPAU surface
|
154 |
+
* format. The mapping is shown in the table below. \p mipLevel must be 0.
|
155 |
+
*
|
156 |
+
* \htmlonly
|
157 |
+
* <table>
|
158 |
+
* <tr><th>VdpChromaType </th><th>arrayIndex</th><th>Size </th><th>Format</th><th>Content </th></tr>
|
159 |
+
* <tr><td rowspan="4" valign="top">VDP_CHROMA_TYPE_420</td><td>0 </td><td>w x h/2</td><td>R8 </td><td>Top-field luma </td></tr>
|
160 |
+
* <tr> <td>1 </td><td>w x h/2</td><td>R8 </td><td>Bottom-field luma </td></tr>
|
161 |
+
* <tr> <td>2 </td><td>w/2 x h/4</td><td>R8G8 </td><td>Top-field chroma </td></tr>
|
162 |
+
* <tr> <td>3 </td><td>w/2 x h/4</td><td>R8G8 </td><td>Bottom-field chroma</td></tr>
|
163 |
+
* <tr><td rowspan="4" valign="top">VDP_CHROMA_TYPE_422</td><td>0 </td><td>w x h/2</td><td>R8 </td><td>Top-field luma </td></tr>
|
164 |
+
* <tr> <td>1 </td><td>w x h/2</td><td>R8 </td><td>Bottom-field luma </td></tr>
|
165 |
+
* <tr> <td>2 </td><td>w/2 x h/2</td><td>R8G8 </td><td>Top-field chroma </td></tr>
|
166 |
+
* <tr> <td>3 </td><td>w/2 x h/2</td><td>R8G8 </td><td>Bottom-field chroma</td></tr>
|
167 |
+
* </table>
|
168 |
+
* \endhtmlonly
|
169 |
+
*
|
170 |
+
* \latexonly
|
171 |
+
* \begin{tabular}{|l|l|l|l|l|}
|
172 |
+
* \hline
|
173 |
+
* VdpChromaType & arrayIndex & Size & Format & Content \\
|
174 |
+
* \hline
|
175 |
+
* VDP\_CHROMA\_TYPE\_420 & 0 & w x h/2 & R8 & Top-field luma \\
|
176 |
+
* & 1 & w x h/2 & R8 & Bottom-field luma \\
|
177 |
+
* & 2 & w/2 x h/4 & R8G8 & Top-field chroma \\
|
178 |
+
* & 3 & w/2 x h/4 & R8G8 & Bottom-field chroma \\
|
179 |
+
* \hline
|
180 |
+
* VDP\_CHROMA\_TYPE\_422 & 0 & w x h/2 & R8 & Top-field luma \\
|
181 |
+
* & 1 & w x h/2 & R8 & Bottom-field luma \\
|
182 |
+
* & 2 & w/2 x h/2 & R8G8 & Top-field chroma \\
|
183 |
+
* & 3 & w/2 x h/2 & R8G8 & Bottom-field chroma \\
|
184 |
+
* \hline
|
185 |
+
* \end{tabular}
|
186 |
+
* \endlatexonly
|
187 |
+
*
|
188 |
+
* \param pCudaResource - Pointer to the returned object handle
|
189 |
+
* \param vdpSurface - The VdpVideoSurface to be registered
|
190 |
+
* \param flags - Map flags
|
191 |
+
*
|
192 |
+
* \return
|
193 |
+
* ::CUDA_SUCCESS,
|
194 |
+
* ::CUDA_ERROR_INVALID_HANDLE,
|
195 |
+
* ::CUDA_ERROR_ALREADY_MAPPED,
|
196 |
+
* ::CUDA_ERROR_INVALID_CONTEXT,
|
197 |
+
* \notefnerr
|
198 |
+
*
|
199 |
+
* \sa ::cuCtxCreate, ::cuVDPAUCtxCreate,
|
200 |
+
* ::cuGraphicsVDPAURegisterOutputSurface, ::cuGraphicsUnregisterResource,
|
201 |
+
* ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
|
202 |
+
* ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
|
203 |
+
* ::cuVDPAUGetDevice,
|
204 |
+
* ::cudaGraphicsVDPAURegisterVideoSurface
|
205 |
+
*/
|
206 |
+
CUresult CUDAAPI cuGraphicsVDPAURegisterVideoSurface(CUgraphicsResource *pCudaResource, VdpVideoSurface vdpSurface, unsigned int flags);
|
207 |
+
|
208 |
+
/**
|
209 |
+
* \brief Registers a VDPAU VdpOutputSurface object
|
210 |
+
*
|
211 |
+
* Registers the VdpOutputSurface specified by \p vdpSurface for access by
|
212 |
+
* CUDA. A handle to the registered object is returned as \p pCudaResource.
|
213 |
+
* The surface's intended usage is specified using \p flags, as follows:
|
214 |
+
*
|
215 |
+
* - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE: Specifies no hints about how this
|
216 |
+
* resource will be used. It is therefore assumed that this resource will be
|
217 |
+
* read from and written to by CUDA. This is the default value.
|
218 |
+
* - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_READ_ONLY: Specifies that CUDA
|
219 |
+
* will not write to this resource.
|
220 |
+
* - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_WRITE_DISCARD: Specifies that
|
221 |
+
* CUDA will not read from this resource and will write over the
|
222 |
+
* entire contents of the resource, so none of the data previously
|
223 |
+
* stored in the resource will be preserved.
|
224 |
+
*
|
225 |
+
* The VdpOutputSurface is presented as an array of subresources that may be
|
226 |
+
* accessed using pointers returned by ::cuGraphicsSubResourceGetMappedArray.
|
227 |
+
* The exact number of valid \p arrayIndex values depends on the VDPAU surface
|
228 |
+
* format. The mapping is shown in the table below. \p mipLevel must be 0.
|
229 |
+
*
|
230 |
+
* \htmlonly
|
231 |
+
* <table>
|
232 |
+
* <tr><th>VdpRGBAFormat </th><th>arrayIndex</th><th>Size </th><th>Format </th><th>Content </th></tr>
|
233 |
+
* <tr><td>VDP_RGBA_FORMAT_B8G8R8A8 </td><td>0 </td><td>w x h</td><td>ARGB8 </td><td>Entire surface</td></tr>
|
234 |
+
* <tr><td>VDP_RGBA_FORMAT_R10G10B10A2</td><td>0 </td><td>w x h</td><td>A2BGR10</td><td>Entire surface</td></tr>
|
235 |
+
* </table>
|
236 |
+
* \endhtmlonly
|
237 |
+
*
|
238 |
+
* \latexonly
|
239 |
+
* \begin{tabular}{|l|l|l|l|l|}
|
240 |
+
* \hline
|
241 |
+
* VdpRGBAFormat & arrayIndex & Size & Format & Content \\
|
242 |
+
* \hline
|
243 |
+
* VDP\_RGBA\_FORMAT\_B8G8R8A8 & 0 & w x h & ARGB8 & Entire surface \\
|
244 |
+
* VDP\_RGBA\_FORMAT\_R10G10B10A2 & 0 & w x h & A2BGR10 & Entire surface \\
|
245 |
+
* \hline
|
246 |
+
* \end{tabular}
|
247 |
+
* \endlatexonly
|
248 |
+
*
|
249 |
+
* \param pCudaResource - Pointer to the returned object handle
|
250 |
+
* \param vdpSurface - The VdpOutputSurface to be registered
|
251 |
+
* \param flags - Map flags
|
252 |
+
*
|
253 |
+
* \return
|
254 |
+
* ::CUDA_SUCCESS,
|
255 |
+
* ::CUDA_ERROR_INVALID_HANDLE,
|
256 |
+
* ::CUDA_ERROR_ALREADY_MAPPED,
|
257 |
+
* ::CUDA_ERROR_INVALID_CONTEXT,
|
258 |
+
* \notefnerr
|
259 |
+
*
|
260 |
+
* \sa ::cuCtxCreate, ::cuVDPAUCtxCreate,
|
261 |
+
* ::cuGraphicsVDPAURegisterVideoSurface, ::cuGraphicsUnregisterResource,
|
262 |
+
* ::cuGraphicsResourceSetMapFlags, ::cuGraphicsMapResources,
|
263 |
+
* ::cuGraphicsUnmapResources, ::cuGraphicsSubResourceGetMappedArray,
|
264 |
+
* ::cuVDPAUGetDevice,
|
265 |
+
* ::cudaGraphicsVDPAURegisterOutputSurface
|
266 |
+
*/
|
267 |
+
CUresult CUDAAPI cuGraphicsVDPAURegisterOutputSurface(CUgraphicsResource *pCudaResource, VdpOutputSurface vdpSurface, unsigned int flags);
|
268 |
+
|
269 |
+
/** @} */ /* END CUDA_VDPAU */
|
270 |
+
|
271 |
+
|
272 |
+
#if defined(__CUDA_API_VERSION_INTERNAL)
|
273 |
+
#undef cuVDPAUCtxCreate
|
274 |
+
|
275 |
+
CUresult CUDAAPI cuVDPAUCtxCreate(CUcontext *pCtx, unsigned int flags, CUdevice device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
|
276 |
+
#endif /* __CUDA_API_VERSION_INTERNAL */
|
277 |
+
|
278 |
+
#ifdef __cplusplus
|
279 |
+
};
|
280 |
+
#endif
|
281 |
+
|
282 |
+
#endif
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_awbarrier.h
ADDED
@@ -0,0 +1,280 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2019 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#ifndef _CUDA_AWBARRIER_H_
|
51 |
+
# define _CUDA_AWBARRIER_H_
|
52 |
+
|
53 |
+
# include "cuda_awbarrier_primitives.h"
|
54 |
+
|
55 |
+
# if !defined(_CUDA_AWBARRIER_SM_TARGET)
|
56 |
+
# error This file requires compute capability 7.0 or greater.
|
57 |
+
# endif
|
58 |
+
|
59 |
+
# if !defined(_CUDA_AWBARRIER_CPLUSPLUS_11_OR_LATER)
|
60 |
+
# error This file requires compiler support for the ISO C++ 2011 standard. This support must be enabled with the \
|
61 |
+
-std=c++11 compiler option.
|
62 |
+
# endif
|
63 |
+
|
64 |
+
_CUDA_AWBARRIER_BEGIN_NAMESPACE
|
65 |
+
|
66 |
+
class awbarrier {
|
67 |
+
public:
|
68 |
+
class arrival_token {
|
69 |
+
public:
|
70 |
+
arrival_token() = default;
|
71 |
+
~arrival_token() = default;
|
72 |
+
_CUDA_AWBARRIER_QUALIFIER uint32_t pending_count() const;
|
73 |
+
private:
|
74 |
+
_CUDA_AWBARRIER_QUALIFIER arrival_token(uint64_t token);
|
75 |
+
uint64_t token;
|
76 |
+
friend awbarrier;
|
77 |
+
};
|
78 |
+
awbarrier() = default;
|
79 |
+
awbarrier(const awbarrier&) = delete;
|
80 |
+
awbarrier& operator=(const awbarrier&) = delete;
|
81 |
+
~awbarrier() = default;
|
82 |
+
|
83 |
+
_CUDA_AWBARRIER_QUALIFIER arrival_token arrive();
|
84 |
+
_CUDA_AWBARRIER_QUALIFIER arrival_token arrive_and_drop();
|
85 |
+
_CUDA_AWBARRIER_QUALIFIER bool timed_wait(arrival_token token, uint32_t hint_cycles);
|
86 |
+
_CUDA_AWBARRIER_QUALIFIER bool timed_wait_parity(bool phase, uint32_t hint_cycles);
|
87 |
+
_CUDA_AWBARRIER_QUALIFIER void wait(arrival_token token);
|
88 |
+
_CUDA_AWBARRIER_QUALIFIER void arrive_and_wait();
|
89 |
+
_CUDA_AWBARRIER_QUALIFIER bool try_wait(arrival_token token, uint32_t maxSleepNanosec);
|
90 |
+
_CUDA_AWBARRIER_QUALIFIER bool try_wait_parity(bool phase, uint32_t maxSleepNanosec);
|
91 |
+
_CUDA_AWBARRIER_STATIC_QUALIFIER __host__ constexpr uint32_t max();
|
92 |
+
|
93 |
+
private:
|
94 |
+
uint64_t barrier;
|
95 |
+
friend _CUDA_AWBARRIER_QUALIFIER void init(awbarrier* barrier, uint32_t expected_count);
|
96 |
+
friend _CUDA_AWBARRIER_QUALIFIER void inval(awbarrier* barrier);
|
97 |
+
friend class pipeline;
|
98 |
+
};
|
99 |
+
|
100 |
+
_CUDA_AWBARRIER_QUALIFIER
|
101 |
+
uint32_t awbarrier::arrival_token::pending_count() const
|
102 |
+
{
|
103 |
+
const uint32_t pending_count = _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_token_pending_count(this->token);
|
104 |
+
#if (__CUDA_ARCH__ >= 900)
|
105 |
+
return pending_count;
|
106 |
+
#else
|
107 |
+
return (pending_count >> 15);
|
108 |
+
#endif
|
109 |
+
}
|
110 |
+
|
111 |
+
_CUDA_AWBARRIER_QUALIFIER
|
112 |
+
awbarrier::arrival_token::arrival_token(uint64_t token)
|
113 |
+
: token(token)
|
114 |
+
{
|
115 |
+
}
|
116 |
+
|
117 |
+
_CUDA_AWBARRIER_QUALIFIER
|
118 |
+
void init(awbarrier* barrier, uint32_t expected_count)
|
119 |
+
{
|
120 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(barrier));
|
121 |
+
_CUDA_AWBARRIER_ASSERT(expected_count > 0 && expected_count <= _CUDA_AWBARRIER_MAX_COUNT);
|
122 |
+
|
123 |
+
#if (__CUDA_ARCH__ >= 900)
|
124 |
+
const uint32_t init_count = expected_count;
|
125 |
+
#else
|
126 |
+
const uint32_t init_count = (expected_count << 15) + expected_count;
|
127 |
+
#endif
|
128 |
+
|
129 |
+
_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_init(&barrier->barrier, init_count);
|
130 |
+
}
|
131 |
+
|
132 |
+
_CUDA_AWBARRIER_QUALIFIER
|
133 |
+
void inval(awbarrier* barrier)
|
134 |
+
{
|
135 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(barrier));
|
136 |
+
|
137 |
+
_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_inval(&barrier->barrier);
|
138 |
+
}
|
139 |
+
|
140 |
+
_CUDA_AWBARRIER_QUALIFIER
|
141 |
+
awbarrier::arrival_token awbarrier::arrive()
|
142 |
+
{
|
143 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
144 |
+
|
145 |
+
#if (__CUDA_ARCH__ < 900)
|
146 |
+
const uint32_t arrive_count = 1 << 15;
|
147 |
+
const uint64_t token = _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_arrive_drop_no_complete<false>(&this->barrier, arrive_count);
|
148 |
+
(void)
|
149 |
+
#else
|
150 |
+
const uint64_t token =
|
151 |
+
#endif
|
152 |
+
_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_arrive_drop<false>(&this->barrier);
|
153 |
+
|
154 |
+
return arrival_token(token);
|
155 |
+
}
|
156 |
+
|
157 |
+
_CUDA_AWBARRIER_QUALIFIER
|
158 |
+
awbarrier::arrival_token awbarrier::arrive_and_drop()
|
159 |
+
{
|
160 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
161 |
+
|
162 |
+
#if (__CUDA_ARCH__ < 900)
|
163 |
+
const uint32_t arrive_count = 1 << 15;
|
164 |
+
const uint64_t token = _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_arrive_drop_no_complete<true>(&this->barrier, arrive_count);
|
165 |
+
(void)
|
166 |
+
#else
|
167 |
+
const uint64_t token =
|
168 |
+
#endif
|
169 |
+
_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_arrive_drop<true>(&this->barrier);
|
170 |
+
|
171 |
+
return arrival_token(token);
|
172 |
+
}
|
173 |
+
|
174 |
+
_CUDA_AWBARRIER_QUALIFIER
|
175 |
+
bool awbarrier::timed_wait(arrival_token token, uint32_t hint_cycles)
|
176 |
+
{
|
177 |
+
constexpr uint64_t max_busy_wait_cycles = 1024;
|
178 |
+
constexpr uint32_t max_sleep_ns = 1 << 20;
|
179 |
+
|
180 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
181 |
+
|
182 |
+
if (_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_test_wait(&this->barrier, token.token)) {
|
183 |
+
return true;
|
184 |
+
}
|
185 |
+
|
186 |
+
uint64_t start_cycles = clock64();
|
187 |
+
uint64_t elapsed_cycles = 0;
|
188 |
+
uint32_t sleep_ns = 32;
|
189 |
+
while (elapsed_cycles < hint_cycles) {
|
190 |
+
if (_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_test_wait(&this->barrier, token.token)) {
|
191 |
+
return true;
|
192 |
+
}
|
193 |
+
|
194 |
+
if (elapsed_cycles > max_busy_wait_cycles) {
|
195 |
+
__nanosleep(sleep_ns);
|
196 |
+
if (sleep_ns < max_sleep_ns) {
|
197 |
+
sleep_ns *= 2;
|
198 |
+
}
|
199 |
+
}
|
200 |
+
|
201 |
+
elapsed_cycles = clock64() - start_cycles;
|
202 |
+
}
|
203 |
+
|
204 |
+
return false;
|
205 |
+
}
|
206 |
+
|
207 |
+
_CUDA_AWBARRIER_QUALIFIER
|
208 |
+
bool awbarrier::timed_wait_parity(bool phase, uint32_t hint_cycles)
|
209 |
+
{
|
210 |
+
constexpr uint64_t max_busy_wait_cycles = 1024;
|
211 |
+
constexpr uint32_t max_sleep_ns = 1 << 20;
|
212 |
+
|
213 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
214 |
+
|
215 |
+
if (_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_test_wait_parity(&this->barrier, phase)) {
|
216 |
+
return true;
|
217 |
+
}
|
218 |
+
|
219 |
+
uint64_t start_cycles = clock64();
|
220 |
+
uint64_t elapsed_cycles = 0;
|
221 |
+
uint32_t sleep_ns = 32;
|
222 |
+
while (elapsed_cycles < hint_cycles) {
|
223 |
+
if (_CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_test_wait_parity(&this->barrier, phase)) {
|
224 |
+
return true;
|
225 |
+
}
|
226 |
+
|
227 |
+
if (elapsed_cycles > max_busy_wait_cycles) {
|
228 |
+
__nanosleep(sleep_ns);
|
229 |
+
if (sleep_ns < max_sleep_ns) {
|
230 |
+
sleep_ns *= 2;
|
231 |
+
}
|
232 |
+
}
|
233 |
+
|
234 |
+
elapsed_cycles = clock64() - start_cycles;
|
235 |
+
}
|
236 |
+
|
237 |
+
return false;
|
238 |
+
}
|
239 |
+
|
240 |
+
_CUDA_AWBARRIER_QUALIFIER
|
241 |
+
bool awbarrier::try_wait(arrival_token token, uint32_t maxSleepNanosec)
|
242 |
+
{
|
243 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
244 |
+
|
245 |
+
return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_try_wait(&this->barrier, token.token, maxSleepNanosec);
|
246 |
+
}
|
247 |
+
|
248 |
+
_CUDA_AWBARRIER_QUALIFIER
|
249 |
+
bool awbarrier::try_wait_parity(bool phase, uint32_t maxSleepNanosec)
|
250 |
+
{
|
251 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
252 |
+
|
253 |
+
return _CUDA_AWBARRIER_INTERNAL_NAMESPACE::awbarrier_try_wait_parity(&this->barrier, phase, maxSleepNanosec);
|
254 |
+
}
|
255 |
+
|
256 |
+
_CUDA_AWBARRIER_QUALIFIER
|
257 |
+
void awbarrier::wait(arrival_token token)
|
258 |
+
{
|
259 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
260 |
+
|
261 |
+
while (!timed_wait(token, ~0u));
|
262 |
+
}
|
263 |
+
|
264 |
+
_CUDA_AWBARRIER_QUALIFIER
|
265 |
+
void awbarrier::arrive_and_wait()
|
266 |
+
{
|
267 |
+
_CUDA_AWBARRIER_ASSERT(__isShared(&this->barrier));
|
268 |
+
|
269 |
+
this->wait(this->arrive());
|
270 |
+
}
|
271 |
+
|
272 |
+
_CUDA_AWBARRIER_QUALIFIER __host__
|
273 |
+
constexpr uint32_t awbarrier::max()
|
274 |
+
{
|
275 |
+
return _CUDA_AWBARRIER_MAX_COUNT;
|
276 |
+
}
|
277 |
+
|
278 |
+
_CUDA_AWBARRIER_END_NAMESPACE
|
279 |
+
|
280 |
+
#endif /* !_CUDA_AWBARRIER_H_ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_fp8.hpp
ADDED
@@ -0,0 +1,1546 @@
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|
1 |
+
/*
|
2 |
+
* Copyright 2022 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__CUDA_FP8_HPP__)
|
51 |
+
#define __CUDA_FP8_HPP__
|
52 |
+
|
53 |
+
#if !defined(__CUDA_FP8_H__)
|
54 |
+
#error "Do not include this file directly. Instead, include cuda_fp8.h."
|
55 |
+
#endif
|
56 |
+
|
57 |
+
/* C++ header for std::memcpy (used for type punning in host-side
|
58 |
+
* implementations). When compiling as a CUDA source file memcpy is provided
|
59 |
+
* implicitly. !defined(__CUDACC__) implies !defined(__CUDACC_RTC__).
|
60 |
+
*/
|
61 |
+
#if defined(__cplusplus) && !defined(__CUDACC__)
|
62 |
+
#include <cstring>
|
63 |
+
#elif !defined(__cplusplus) && !defined(__CUDACC__)
|
64 |
+
#include <string.h>
|
65 |
+
#endif /* defined(__cplusplus) && !defined(__CUDACC__) */
|
66 |
+
|
67 |
+
/* Set up structure-alignment attribute */
|
68 |
+
#if !(defined __CUDA_ALIGN__)
|
69 |
+
#if defined(__CUDACC__)
|
70 |
+
#define __CUDA_ALIGN__(align) __align__(align)
|
71 |
+
#else
|
72 |
+
/* Define alignment macro based on compiler type (cannot assume C11 "_Alignas"
|
73 |
+
* is available) */
|
74 |
+
#if __cplusplus >= 201103L
|
75 |
+
#define __CUDA_ALIGN__(n) \
|
76 |
+
alignas(n) /* C++11 kindly gives us a keyword for this */
|
77 |
+
#else /* !defined(__CPP_VERSION_AT_LEAST_11_FP8)*/
|
78 |
+
#if defined(__GNUC__)
|
79 |
+
#define __CUDA_ALIGN__(n) __attribute__((aligned(n)))
|
80 |
+
#elif defined(_MSC_VER)
|
81 |
+
#define __CUDA_ALIGN__(n) __declspec(align(n))
|
82 |
+
#else
|
83 |
+
#define __CUDA_ALIGN__(n)
|
84 |
+
#endif /* defined(__GNUC__) */
|
85 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
86 |
+
#endif /* defined(__CUDACC__) */
|
87 |
+
#endif /* !(defined __CUDA_ALIGN__) */
|
88 |
+
|
89 |
+
#if !(defined __CPP_VERSION_AT_LEAST_11_FP8)
|
90 |
+
/* need c++11 for explicit operators */
|
91 |
+
#define __CUDA_NO_FP8_CONVERSION_OPERATORS__
|
92 |
+
#endif
|
93 |
+
|
94 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t
|
95 |
+
__nv_cvt_double_to_fp8(const double x, const __nv_saturation_t saturate,
|
96 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
97 |
+
unsigned char res;
|
98 |
+
unsigned long long int xbits;
|
99 |
+
|
100 |
+
#if defined(__CUDACC__) || (!defined __cplusplus)
|
101 |
+
(void)memcpy(&xbits, &x, sizeof(x));
|
102 |
+
#else
|
103 |
+
(void)std::memcpy(&xbits, &x, sizeof(x));
|
104 |
+
#endif
|
105 |
+
unsigned char FP8_MAXNORM;
|
106 |
+
unsigned char FP8_MANTISSA_MASK;
|
107 |
+
unsigned short int FP8_EXP_BIAS;
|
108 |
+
unsigned long long int FP8_SIGNIFICAND_BITS;
|
109 |
+
const unsigned long long int DP_INF_BITS = 0x7FF0000000000000ULL;
|
110 |
+
unsigned long long int FP8_MINDENORM_O2;
|
111 |
+
unsigned long long int FP8_OVERFLOW_THRESHOLD;
|
112 |
+
unsigned long long int FP8_MINNORM;
|
113 |
+
|
114 |
+
if (fp8_interpretation == __NV_E4M3) {
|
115 |
+
FP8_EXP_BIAS = 7U;
|
116 |
+
FP8_SIGNIFICAND_BITS = 4ULL;
|
117 |
+
FP8_MANTISSA_MASK = 0x7U;
|
118 |
+
FP8_MINDENORM_O2 = 0x3F50000000000000ULL; // mindenorm/2 = 2^-10
|
119 |
+
FP8_OVERFLOW_THRESHOLD =
|
120 |
+
0x407D000000000000ULL; // maxnorm + 1/2ulp = 0x1.Cp+8 + 0x1p+4
|
121 |
+
FP8_MAXNORM = 0x7EU;
|
122 |
+
FP8_MINNORM = 0x3F90000000000000ULL; // minnorm = 2^-6
|
123 |
+
} else { //__NV_E5M2
|
124 |
+
FP8_EXP_BIAS = 15U;
|
125 |
+
FP8_SIGNIFICAND_BITS = 3ULL;
|
126 |
+
FP8_MANTISSA_MASK = 0x3U;
|
127 |
+
FP8_MINDENORM_O2 = 0x3EE0000000000000ULL; // mindenorm/2 = 2^-17
|
128 |
+
FP8_OVERFLOW_THRESHOLD =
|
129 |
+
0x40EE000000000000ULL -
|
130 |
+
1ULL; // maxnorm + 1/2ulp = 0x1.Ep+15, and -1 to have common code
|
131 |
+
FP8_MAXNORM = 0x7BU;
|
132 |
+
FP8_MINNORM = 0x3F10000000000000ULL; // minnorm = 2^-14
|
133 |
+
}
|
134 |
+
|
135 |
+
// 1/2 LSB of the target format, positioned in double precision mantissa
|
136 |
+
// helpful in midpoints detection during round-to-nearest-even step
|
137 |
+
const unsigned long long int FP8_DP_HALF_ULP =
|
138 |
+
(unsigned long long int)1ULL << (53ULL - FP8_SIGNIFICAND_BITS - 1ULL);
|
139 |
+
// prepare sign bit in target format
|
140 |
+
unsigned char sign = (unsigned char)((xbits >> 63ULL) << 7U);
|
141 |
+
// prepare exponent field in target format
|
142 |
+
unsigned char exp =
|
143 |
+
(unsigned char)((((unsigned short int)(xbits >> 52ULL)) & 0x7FFU) -
|
144 |
+
1023U + FP8_EXP_BIAS);
|
145 |
+
// round mantissa to target format width, rounding towards zero
|
146 |
+
unsigned char mantissa =
|
147 |
+
(unsigned char)(xbits >> (53ULL - FP8_SIGNIFICAND_BITS)) &
|
148 |
+
FP8_MANTISSA_MASK;
|
149 |
+
unsigned long long int absx = xbits & 0x7FFFFFFFFFFFFFFFULL;
|
150 |
+
|
151 |
+
if (absx <= FP8_MINDENORM_O2) {
|
152 |
+
// zero or underflow
|
153 |
+
res = 0U;
|
154 |
+
} else if (absx > DP_INF_BITS) {
|
155 |
+
// NaN
|
156 |
+
if (fp8_interpretation == __NV_E4M3) {
|
157 |
+
res = 0x7FU;
|
158 |
+
} else {
|
159 |
+
// NaN --> QNaN
|
160 |
+
res = 0x7EU | mantissa;
|
161 |
+
}
|
162 |
+
} else if (absx > FP8_OVERFLOW_THRESHOLD) {
|
163 |
+
if (saturate == __NV_SATFINITE) {
|
164 |
+
res = FP8_MAXNORM;
|
165 |
+
} else {
|
166 |
+
// __NV_NOSAT
|
167 |
+
if (fp8_interpretation == __NV_E4M3) {
|
168 |
+
// no Inf in E4M3
|
169 |
+
res = 0x7FU; // NaN
|
170 |
+
} else {
|
171 |
+
res = 0x7CU; // Inf in E5M2
|
172 |
+
}
|
173 |
+
}
|
174 |
+
} else if (absx >= FP8_MINNORM) {
|
175 |
+
res = (unsigned char)((exp << (FP8_SIGNIFICAND_BITS - 1U)) | mantissa);
|
176 |
+
// rounded-off bits
|
177 |
+
unsigned long long int round =
|
178 |
+
xbits & ((FP8_DP_HALF_ULP << 1ULL) - 1ULL);
|
179 |
+
// round-to-nearest-even adjustment
|
180 |
+
if ((round > FP8_DP_HALF_ULP) ||
|
181 |
+
((round == FP8_DP_HALF_ULP) && (mantissa & 1U))) {
|
182 |
+
res = (unsigned char)(res + 1U);
|
183 |
+
}
|
184 |
+
} else // Denormal range
|
185 |
+
{
|
186 |
+
unsigned char shift = (unsigned char)(1U - exp);
|
187 |
+
// add implicit leading bit
|
188 |
+
mantissa |= (unsigned char)(1U << (FP8_SIGNIFICAND_BITS - 1U));
|
189 |
+
// additional round-off due to denormalization
|
190 |
+
res = (unsigned char)(mantissa >> shift);
|
191 |
+
|
192 |
+
// rounded-off bits, including implicit leading bit
|
193 |
+
unsigned long long int round =
|
194 |
+
(xbits | ((unsigned long long int)1ULL << (53ULL - 1ULL))) &
|
195 |
+
((FP8_DP_HALF_ULP << (shift + 1ULL)) - 1ULL);
|
196 |
+
// round-to-nearest-even adjustment
|
197 |
+
if ((round > (FP8_DP_HALF_ULP << shift)) ||
|
198 |
+
((round == (FP8_DP_HALF_ULP << shift)) && (res & 1U))) {
|
199 |
+
res = (unsigned char)(res + 1U);
|
200 |
+
}
|
201 |
+
}
|
202 |
+
|
203 |
+
res |= sign;
|
204 |
+
|
205 |
+
return (__nv_fp8_storage_t)res;
|
206 |
+
}
|
207 |
+
|
208 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t
|
209 |
+
__nv_cvt_double2_to_fp8x2(const double2 x, const __nv_saturation_t saturate,
|
210 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
211 |
+
__nv_fp8x2_storage_t storage = (__nv_fp8x2_storage_t)__nv_cvt_double_to_fp8(
|
212 |
+
x.y, saturate, fp8_interpretation);
|
213 |
+
storage = (__nv_fp8x2_storage_t)(storage << 8U);
|
214 |
+
storage = (__nv_fp8x2_storage_t)(storage |
|
215 |
+
__nv_cvt_double_to_fp8(
|
216 |
+
x.x, saturate, fp8_interpretation));
|
217 |
+
return storage;
|
218 |
+
}
|
219 |
+
|
220 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t
|
221 |
+
__nv_cvt_float_to_fp8(const float x, const __nv_saturation_t saturate,
|
222 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
223 |
+
__nv_fp8_storage_t res = 0U;
|
224 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
|
225 |
+
if (saturate == __NV_SATFINITE) {
|
226 |
+
__nv_fp8x2_storage_t storage;
|
227 |
+
if (fp8_interpretation == __NV_E5M2) {
|
228 |
+
asm("{cvt.rn.satfinite.e5m2x2.f32 %0, %2, %1;}\n"
|
229 |
+
: "=h"(storage)
|
230 |
+
: "f"(x), "f"(0.0f));
|
231 |
+
} else {
|
232 |
+
asm("{cvt.rn.satfinite.e4m3x2.f32 %0, %2, %1;}\n"
|
233 |
+
: "=h"(storage)
|
234 |
+
: "f"(x), "f"(0.0f));
|
235 |
+
}
|
236 |
+
res = (__nv_fp8_storage_t)storage;
|
237 |
+
} else
|
238 |
+
#endif
|
239 |
+
{
|
240 |
+
unsigned int xbits;
|
241 |
+
#if defined(__CUDACC__) || (!defined __cplusplus)
|
242 |
+
(void)memcpy(&xbits, &x, sizeof(x));
|
243 |
+
#else
|
244 |
+
(void)std::memcpy(&xbits, &x, sizeof(x));
|
245 |
+
#endif
|
246 |
+
|
247 |
+
// isnan
|
248 |
+
if ((xbits & 0x7FFFFFFFU) > 0x7F800000U) {
|
249 |
+
// Canonical NaN
|
250 |
+
xbits = 0x7FFFFFFFU;
|
251 |
+
}
|
252 |
+
|
253 |
+
float fx;
|
254 |
+
#if defined(__CUDACC__) || (!defined __cplusplus)
|
255 |
+
(void)memcpy(&fx, &xbits, sizeof(xbits));
|
256 |
+
#else
|
257 |
+
(void)std::memcpy(&fx, &xbits, sizeof(xbits));
|
258 |
+
#endif
|
259 |
+
|
260 |
+
const double dx = (double)fx;
|
261 |
+
res = __nv_cvt_double_to_fp8(dx, saturate, fp8_interpretation);
|
262 |
+
}
|
263 |
+
return res;
|
264 |
+
}
|
265 |
+
|
266 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t
|
267 |
+
__nv_cvt_float2_to_fp8x2(const float2 x, const __nv_saturation_t saturate,
|
268 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
269 |
+
__nv_fp8x2_storage_t storage;
|
270 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
|
271 |
+
if (saturate == __NV_SATFINITE) {
|
272 |
+
if (fp8_interpretation == __NV_E5M2) {
|
273 |
+
asm("{cvt.rn.satfinite.e5m2x2.f32 %0, %2, %1;}\n"
|
274 |
+
: "=h"(storage)
|
275 |
+
: "f"(x.x), "f"(x.y));
|
276 |
+
} else {
|
277 |
+
asm("{cvt.rn.satfinite.e4m3x2.f32 %0, %2, %1;}\n"
|
278 |
+
: "=h"(storage)
|
279 |
+
: "f"(x.x), "f"(x.y));
|
280 |
+
}
|
281 |
+
} else
|
282 |
+
#endif
|
283 |
+
{
|
284 |
+
storage = (__nv_fp8x2_storage_t)__nv_cvt_float_to_fp8(
|
285 |
+
x.y, saturate, fp8_interpretation);
|
286 |
+
storage = (__nv_fp8x2_storage_t)(storage << 8U);
|
287 |
+
storage = (__nv_fp8x2_storage_t)(storage | __nv_cvt_float_to_fp8(
|
288 |
+
x.x, saturate,
|
289 |
+
fp8_interpretation));
|
290 |
+
}
|
291 |
+
return storage;
|
292 |
+
}
|
293 |
+
|
294 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ float
|
295 |
+
__internal_halfraw_to_float(const __half_raw x) {
|
296 |
+
float f;
|
297 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 530)
|
298 |
+
asm("{cvt.f32.f16 %0, %1;}\n" : "=f"(f) : "h"(x.x));
|
299 |
+
#else
|
300 |
+
const unsigned int ux = (unsigned int)x.x;
|
301 |
+
unsigned int sign = (ux >> 15U) & 1U;
|
302 |
+
unsigned int exponent = (ux >> 10U) & 0x1fU;
|
303 |
+
unsigned int mantissa = (ux & 0x3ffU) << 13U;
|
304 |
+
if (exponent == 0x1fU) { /* NaN or Inf */
|
305 |
+
/* discard sign of a NaN */
|
306 |
+
sign = ((mantissa != 0U) ? (sign >> 1U) : sign);
|
307 |
+
mantissa = ((mantissa != 0U) ? 0x7fffffU : 0U);
|
308 |
+
exponent = 0xffU;
|
309 |
+
} else if (exponent == 0U) { /* Denorm or Zero */
|
310 |
+
if (mantissa != 0U) {
|
311 |
+
unsigned int msb;
|
312 |
+
exponent = 0x71U;
|
313 |
+
do {
|
314 |
+
msb = (mantissa & 0x400000U);
|
315 |
+
mantissa <<= 1U; /* normalize */
|
316 |
+
--exponent;
|
317 |
+
} while (msb == 0U);
|
318 |
+
mantissa &= 0x7fffffU; /* 1.mantissa is implicit */
|
319 |
+
}
|
320 |
+
} else {
|
321 |
+
exponent += 0x70U;
|
322 |
+
}
|
323 |
+
const unsigned int u = ((sign << 31U) | (exponent << 23U) | mantissa);
|
324 |
+
#if defined(__CUDACC__) || (!defined __cplusplus)
|
325 |
+
(void)memcpy(&f, &u, sizeof(u));
|
326 |
+
#else
|
327 |
+
(void)std::memcpy(&f, &u, sizeof(u));
|
328 |
+
#endif
|
329 |
+
#endif /* (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 530) */
|
330 |
+
return f;
|
331 |
+
}
|
332 |
+
|
333 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ float2
|
334 |
+
__internal_halfraw2_to_float2(const __half2_raw x) {
|
335 |
+
__half_raw raw;
|
336 |
+
float2 res;
|
337 |
+
raw.x = x.x;
|
338 |
+
res.x = __internal_halfraw_to_float(raw);
|
339 |
+
raw.x = x.y;
|
340 |
+
res.y = __internal_halfraw_to_float(raw);
|
341 |
+
return res;
|
342 |
+
}
|
343 |
+
|
344 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t
|
345 |
+
__nv_cvt_halfraw_to_fp8(const __half_raw x, const __nv_saturation_t saturate,
|
346 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
347 |
+
__nv_fp8_storage_t res = 0U;
|
348 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
|
349 |
+
if (saturate == __NV_SATFINITE) {
|
350 |
+
unsigned int half2_storage = (unsigned int)(x.x);
|
351 |
+
__nv_fp8x2_storage_t tmp;
|
352 |
+
if (fp8_interpretation == __NV_E5M2) {
|
353 |
+
asm("{cvt.rn.satfinite.e5m2x2.f16x2 %0, %1;}\n"
|
354 |
+
: "=h"(tmp)
|
355 |
+
: "r"(half2_storage));
|
356 |
+
} else {
|
357 |
+
asm("{cvt.rn.satfinite.e4m3x2.f16x2 %0, %1;}\n"
|
358 |
+
: "=h"(tmp)
|
359 |
+
: "r"(half2_storage));
|
360 |
+
}
|
361 |
+
res = (__nv_fp8_storage_t)tmp;
|
362 |
+
} else
|
363 |
+
#endif
|
364 |
+
{
|
365 |
+
float fx = __internal_halfraw_to_float(x);
|
366 |
+
res = __nv_cvt_float_to_fp8(fx, saturate, fp8_interpretation);
|
367 |
+
}
|
368 |
+
return res;
|
369 |
+
}
|
370 |
+
|
371 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t __nv_cvt_halfraw2_to_fp8x2(
|
372 |
+
const __half2_raw x, const __nv_saturation_t saturate,
|
373 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
374 |
+
__nv_fp8x2_storage_t tmp;
|
375 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
|
376 |
+
if (saturate == __NV_SATFINITE) {
|
377 |
+
unsigned int half2_storage;
|
378 |
+
(void)memcpy(&half2_storage, &x, sizeof(x));
|
379 |
+
|
380 |
+
if (fp8_interpretation == __NV_E5M2) {
|
381 |
+
asm("{cvt.rn.satfinite.e5m2x2.f16x2 %0, %1;}\n"
|
382 |
+
: "=h"(tmp)
|
383 |
+
: "r"(half2_storage));
|
384 |
+
} else {
|
385 |
+
asm("{cvt.rn.satfinite.e4m3x2.f16x2 %0, %1;}\n"
|
386 |
+
: "=h"(tmp)
|
387 |
+
: "r"(half2_storage));
|
388 |
+
}
|
389 |
+
} else
|
390 |
+
#endif
|
391 |
+
{
|
392 |
+
__half_raw raw;
|
393 |
+
raw.x = x.x;
|
394 |
+
__nv_fp8_storage_t lo =
|
395 |
+
__nv_cvt_halfraw_to_fp8(raw, saturate, fp8_interpretation);
|
396 |
+
raw.x = x.y;
|
397 |
+
__nv_fp8_storage_t hi =
|
398 |
+
__nv_cvt_halfraw_to_fp8(raw, saturate, fp8_interpretation);
|
399 |
+
tmp = hi;
|
400 |
+
tmp = (__nv_fp8x2_storage_t)(tmp << 8U);
|
401 |
+
tmp = (__nv_fp8x2_storage_t)(tmp | lo);
|
402 |
+
}
|
403 |
+
return tmp;
|
404 |
+
}
|
405 |
+
|
406 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ float
|
407 |
+
__internal_bf16raw_to_float(const __nv_bfloat16_raw x) {
|
408 |
+
const unsigned int ux = ((unsigned int)x.x) << 16U;
|
409 |
+
float fx;
|
410 |
+
#if defined(__CUDACC__) || (!defined __cplusplus)
|
411 |
+
(void)memcpy(&fx, &ux, sizeof(ux));
|
412 |
+
#else
|
413 |
+
(void)std::memcpy(&fx, &ux, sizeof(ux));
|
414 |
+
#endif
|
415 |
+
return fx;
|
416 |
+
}
|
417 |
+
|
418 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_bfloat16_raw
|
419 |
+
__internal_float_to_bf16raw_rz(const float x) {
|
420 |
+
unsigned int ux;
|
421 |
+
__nv_bfloat16_raw r;
|
422 |
+
#if defined(__CUDACC__) || (!defined __cplusplus)
|
423 |
+
(void)memcpy(&ux, &x, sizeof(x));
|
424 |
+
#else
|
425 |
+
(void)std::memcpy(&ux, &x, sizeof(x));
|
426 |
+
#endif
|
427 |
+
r.x = (unsigned short int)(ux >> 16U);
|
428 |
+
return r;
|
429 |
+
}
|
430 |
+
|
431 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8_storage_t __nv_cvt_bfloat16raw_to_fp8(
|
432 |
+
const __nv_bfloat16_raw x, const __nv_saturation_t saturate,
|
433 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
434 |
+
const float fx = __internal_bf16raw_to_float(x);
|
435 |
+
const __nv_fp8_storage_t res =
|
436 |
+
__nv_cvt_float_to_fp8(fx, saturate, fp8_interpretation);
|
437 |
+
return res;
|
438 |
+
}
|
439 |
+
|
440 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __nv_fp8x2_storage_t
|
441 |
+
__nv_cvt_bfloat16raw2_to_fp8x2(
|
442 |
+
const __nv_bfloat162_raw x, const __nv_saturation_t saturate,
|
443 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
444 |
+
__nv_bfloat16_raw raw;
|
445 |
+
raw.x = x.y;
|
446 |
+
__nv_fp8x2_storage_t storage =
|
447 |
+
(__nv_fp8x2_storage_t)__nv_cvt_bfloat16raw_to_fp8(raw, saturate,
|
448 |
+
fp8_interpretation);
|
449 |
+
storage = (__nv_fp8x2_storage_t)(storage << 8U);
|
450 |
+
raw.x = x.x;
|
451 |
+
storage = (__nv_fp8x2_storage_t)(storage |
|
452 |
+
__nv_cvt_bfloat16raw_to_fp8(
|
453 |
+
raw, saturate, fp8_interpretation));
|
454 |
+
return storage;
|
455 |
+
}
|
456 |
+
|
457 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __half2_raw
|
458 |
+
__nv_cvt_fp8x2_to_halfraw2(const __nv_fp8x2_storage_t x,
|
459 |
+
const __nv_fp8_interpretation_t fp8_interpretation);
|
460 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __half_raw
|
461 |
+
__nv_cvt_fp8_to_halfraw(const __nv_fp8_storage_t x,
|
462 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
463 |
+
__half_raw res;
|
464 |
+
res.x = 0U;
|
465 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
|
466 |
+
res.x =
|
467 |
+
__nv_cvt_fp8x2_to_halfraw2((__nv_fp8x2_storage_t)x, fp8_interpretation)
|
468 |
+
.x;
|
469 |
+
#else
|
470 |
+
unsigned short int ur = (unsigned short int)x;
|
471 |
+
ur = (unsigned short int)(ur << 8U);
|
472 |
+
|
473 |
+
if (fp8_interpretation == __NV_E5M2) {
|
474 |
+
if ((ur & 0x7FFFU) > 0x7C00U) {
|
475 |
+
/* If NaN, return canonical NaN */
|
476 |
+
ur = 0x7FFFU;
|
477 |
+
}
|
478 |
+
} else { // __NV_E4M3
|
479 |
+
unsigned short int sign = ur & 0x8000U;
|
480 |
+
unsigned short int exponent =
|
481 |
+
(unsigned short int)(((ur & 0x7800U) >> 1U) + 0x2000U);
|
482 |
+
unsigned short int mantissa = (ur & 0x0700U) >> 1U;
|
483 |
+
unsigned char absx = 0x7FU & (unsigned char)x;
|
484 |
+
|
485 |
+
if (absx == 0x7FU) // NaN
|
486 |
+
{
|
487 |
+
ur = 0x7FFFU; // fp16 canonical NaN, discard sign
|
488 |
+
} else if (exponent == 0x2000U) {
|
489 |
+
// zero or denormal
|
490 |
+
if (mantissa != 0U) {
|
491 |
+
// normalize
|
492 |
+
mantissa = (unsigned short int)(mantissa << 1U);
|
493 |
+
while ((mantissa & 0x0400U) == 0U) {
|
494 |
+
mantissa = (unsigned short int)(mantissa << 1U);
|
495 |
+
exponent = (unsigned short int)(exponent - 0x0400U);
|
496 |
+
}
|
497 |
+
// discard implicit leading bit
|
498 |
+
mantissa &= 0x03FFU;
|
499 |
+
} else { // Zero
|
500 |
+
exponent = 0U;
|
501 |
+
}
|
502 |
+
|
503 |
+
ur = (sign | exponent) | mantissa;
|
504 |
+
} else {
|
505 |
+
ur = (sign | exponent) | mantissa;
|
506 |
+
}
|
507 |
+
}
|
508 |
+
res.x = ur;
|
509 |
+
#endif
|
510 |
+
return res;
|
511 |
+
}
|
512 |
+
|
513 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ __half2_raw
|
514 |
+
__nv_cvt_fp8x2_to_halfraw2(const __nv_fp8x2_storage_t x,
|
515 |
+
const __nv_fp8_interpretation_t fp8_interpretation) {
|
516 |
+
__half2_raw res;
|
517 |
+
#if (defined __CUDA_ARCH__) && (__CUDA_ARCH__ >= 890)
|
518 |
+
unsigned int half2_storage;
|
519 |
+
if (fp8_interpretation == __NV_E5M2) {
|
520 |
+
asm("{cvt.rn.f16x2.e5m2x2 %0, %1;}\n" : "=r"(half2_storage) : "h"(x));
|
521 |
+
} else {
|
522 |
+
asm("{cvt.rn.f16x2.e4m3x2 %0, %1;}\n" : "=r"(half2_storage) : "h"(x));
|
523 |
+
}
|
524 |
+
(void)memcpy(&res, &half2_storage, sizeof(half2_storage));
|
525 |
+
#else
|
526 |
+
res.x =
|
527 |
+
__nv_cvt_fp8_to_halfraw((__nv_fp8_storage_t)x, fp8_interpretation).x;
|
528 |
+
res.y = __nv_cvt_fp8_to_halfraw((__nv_fp8_storage_t)(x >> 8U),
|
529 |
+
fp8_interpretation)
|
530 |
+
.x;
|
531 |
+
#endif
|
532 |
+
return res;
|
533 |
+
}
|
534 |
+
|
535 |
+
/* All other definitions in this file are only visible to C++ compilers */
|
536 |
+
#if defined(__cplusplus)
|
537 |
+
|
538 |
+
/**
|
539 |
+
* \defgroup CUDA_MATH_FP8_E5M2_STRUCT C++ struct for handling fp8 data type of e5m2 kind.
|
540 |
+
* \ingroup CUDA_MATH_INTRINSIC_FP8
|
541 |
+
*/
|
542 |
+
|
543 |
+
/**
|
544 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
545 |
+
* \brief __nv_fp8_e5m2 datatype
|
546 |
+
*
|
547 |
+
* \details This structure implements the datatype for handling
|
548 |
+
* \p fp8 floating-point numbers of \p e5m2 kind:
|
549 |
+
* with 1 sign, 5 exponent, 1 implicit and 2 explicit mantissa bits.
|
550 |
+
*
|
551 |
+
* The structure implements converting constructors and operators.
|
552 |
+
*/
|
553 |
+
struct __CUDA_ALIGN__(1) __nv_fp8_e5m2 {
|
554 |
+
public:
|
555 |
+
/**
|
556 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
557 |
+
* Storage variable contains the \p fp8 floating-point data.
|
558 |
+
*/
|
559 |
+
__nv_fp8_storage_t __x;
|
560 |
+
|
561 |
+
/**
|
562 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
563 |
+
* Constructor by default.
|
564 |
+
*/
|
565 |
+
#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
|
566 |
+
__nv_fp8_e5m2() = default;
|
567 |
+
#else
|
568 |
+
__CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2() {}
|
569 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
570 |
+
|
571 |
+
#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
|
572 |
+
|
573 |
+
/* Construct from wider FP types */
|
574 |
+
/* Note we do avoid constructor init-list because of special host/device
|
575 |
+
* compilation rules */
|
576 |
+
|
577 |
+
/**
|
578 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
579 |
+
* Constructor from \p __half data type, relies on \p __NV_SATFINITE
|
580 |
+
* behavior for out-of-range values.
|
581 |
+
*/
|
582 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const __half f) {
|
583 |
+
__x = __nv_cvt_halfraw_to_fp8(static_cast<__half_raw>(f),
|
584 |
+
__NV_SATFINITE, __NV_E5M2);
|
585 |
+
}
|
586 |
+
/**
|
587 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
588 |
+
* Constructor from \p __nv_bfloat16 data type, relies on \p __NV_SATFINITE
|
589 |
+
* behavior for out-of-range values.
|
590 |
+
*/
|
591 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const __nv_bfloat16 f) {
|
592 |
+
__x = __nv_cvt_bfloat16raw_to_fp8(static_cast<__nv_bfloat16_raw>(f),
|
593 |
+
__NV_SATFINITE, __NV_E5M2);
|
594 |
+
}
|
595 |
+
/**
|
596 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
597 |
+
* Constructor from \p float data type, relies on \p __NV_SATFINITE behavior
|
598 |
+
* for out-of-range values.
|
599 |
+
*/
|
600 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const float f) {
|
601 |
+
__x = __nv_cvt_float_to_fp8(f, __NV_SATFINITE, __NV_E5M2);
|
602 |
+
}
|
603 |
+
/**
|
604 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
605 |
+
* Constructor from \p double data type, relies on \p __NV_SATFINITE
|
606 |
+
* behavior for out-of-range values.
|
607 |
+
*/
|
608 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const double f) {
|
609 |
+
__x = __nv_cvt_double_to_fp8(f, __NV_SATFINITE, __NV_E5M2);
|
610 |
+
}
|
611 |
+
|
612 |
+
/* Converts from integral */
|
613 |
+
|
614 |
+
/**
|
615 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
616 |
+
* Constructor from \p unsigned \p short \p int data type, relies on \p
|
617 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
618 |
+
*/
|
619 |
+
explicit __CUDA_HOSTDEVICE_FP8__
|
620 |
+
__nv_fp8_e5m2(const unsigned short int val) {
|
621 |
+
__x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
|
622 |
+
}
|
623 |
+
/**
|
624 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
625 |
+
* Constructor from \p unsigned \p int data type, relies on \p
|
626 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
627 |
+
*/
|
628 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const unsigned int val) {
|
629 |
+
__x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
|
630 |
+
}
|
631 |
+
/**
|
632 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
633 |
+
* Constructor from \p unsigned \p long \p long \p int data type, relies on
|
634 |
+
* \p __NV_SATFINITE behavior for out-of-range values.
|
635 |
+
*/
|
636 |
+
explicit __CUDA_HOSTDEVICE_FP8__
|
637 |
+
__nv_fp8_e5m2(const unsigned long long int val) {
|
638 |
+
__x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
|
639 |
+
}
|
640 |
+
|
641 |
+
/**
|
642 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
643 |
+
* Constructor from \p short \p int data type.
|
644 |
+
*/
|
645 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const short int val) {
|
646 |
+
__x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
|
647 |
+
}
|
648 |
+
/**
|
649 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
650 |
+
* Constructor from \p int data type, relies on \p __NV_SATFINITE behavior
|
651 |
+
* for out-of-range values.
|
652 |
+
*/
|
653 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const int val) {
|
654 |
+
__x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
|
655 |
+
}
|
656 |
+
/**
|
657 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
658 |
+
* Constructor from \p long \p long \p int data type, relies on \p
|
659 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
660 |
+
*/
|
661 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e5m2(const long long int val) {
|
662 |
+
__x = static_cast<__nv_fp8_e5m2>(static_cast<float>(val)).__x;
|
663 |
+
}
|
664 |
+
|
665 |
+
#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
|
666 |
+
/* Widening FP converts */
|
667 |
+
/**
|
668 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
669 |
+
* Conversion operator to \p __half data type.
|
670 |
+
*/
|
671 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator __half() const {
|
672 |
+
return static_cast<__half>(__nv_cvt_fp8_to_halfraw(__x, __NV_E5M2));
|
673 |
+
}
|
674 |
+
/**
|
675 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
676 |
+
* Conversion operator to \p float data type.
|
677 |
+
*/
|
678 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator float() const {
|
679 |
+
return __internal_halfraw_to_float(
|
680 |
+
__nv_cvt_fp8_to_halfraw(__x, __NV_E5M2));
|
681 |
+
}
|
682 |
+
/**
|
683 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
684 |
+
* Conversion operator to \p __nv_bfloat16 data type.
|
685 |
+
*/
|
686 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator __nv_bfloat16() const {
|
687 |
+
return static_cast<__nv_bfloat16>(
|
688 |
+
__internal_float_to_bf16raw_rz(float(*this)));
|
689 |
+
}
|
690 |
+
/**
|
691 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
692 |
+
* Conversion operator to \p double data type.
|
693 |
+
*/
|
694 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator double() const {
|
695 |
+
return static_cast<double>(float(*this));
|
696 |
+
}
|
697 |
+
|
698 |
+
/* Convert to integral */
|
699 |
+
|
700 |
+
/**
|
701 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
702 |
+
* Conversion operator to \p unsigned \p char data type.
|
703 |
+
* Clamps negative and too large inputs to the output range.
|
704 |
+
* \p NaN inputs convert to \p zero.
|
705 |
+
*/
|
706 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned char() const {
|
707 |
+
unsigned char i;
|
708 |
+
const float f = float(*this);
|
709 |
+
const unsigned char max_val = 0xFFU;
|
710 |
+
const unsigned char min_val = 0U;
|
711 |
+
const unsigned char bits = (*this).__x;
|
712 |
+
// saturation fixup
|
713 |
+
if ((bits & 0x7FU) > 0x7CU) {
|
714 |
+
// NaN
|
715 |
+
i = 0;
|
716 |
+
} else if (f > static_cast<float>(max_val)) {
|
717 |
+
// saturate maximum
|
718 |
+
i = max_val;
|
719 |
+
} else if (f < static_cast<float>(min_val)) {
|
720 |
+
// saturate minimum
|
721 |
+
i = min_val;
|
722 |
+
} else {
|
723 |
+
// normal value
|
724 |
+
i = static_cast<unsigned char>(f);
|
725 |
+
}
|
726 |
+
return i;
|
727 |
+
}
|
728 |
+
/**
|
729 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
730 |
+
* Conversion operator to \p unsigned \p short \p int data type.
|
731 |
+
* Clamps negative and too large inputs to the output range.
|
732 |
+
* \p NaN inputs convert to \p zero.
|
733 |
+
*/
|
734 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned short int() const {
|
735 |
+
return __half2ushort_rz(__half(*this));
|
736 |
+
}
|
737 |
+
/**
|
738 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
739 |
+
* Conversion operator to \p unsigned \p int data type.
|
740 |
+
* Clamps negative and too large inputs to the output range.
|
741 |
+
* \p NaN inputs convert to \p zero.
|
742 |
+
*/
|
743 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned int() const {
|
744 |
+
return __half2uint_rz(__half(*this));
|
745 |
+
}
|
746 |
+
/**
|
747 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
748 |
+
* Conversion operator to \p unsigned \p long \p long \p int data type.
|
749 |
+
* Clamps negative and too large inputs to the output range.
|
750 |
+
* \p NaN inputs convert to \p 0x8000000000000000ULL.
|
751 |
+
*/
|
752 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned long long int() const {
|
753 |
+
return __half2ull_rz(__half(*this));
|
754 |
+
}
|
755 |
+
|
756 |
+
/**
|
757 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
758 |
+
* Conversion operator to \p signed \p char data type.
|
759 |
+
* Clamps too large inputs to the output range.
|
760 |
+
* \p NaN inputs convert to \p zero.
|
761 |
+
*/
|
762 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator signed char() const {
|
763 |
+
signed char i;
|
764 |
+
const float f = float(*this);
|
765 |
+
const signed char max_val = (signed char)0x7FU;
|
766 |
+
const signed char min_val = (signed char)0x80U;
|
767 |
+
const unsigned char bits = (*this).__x;
|
768 |
+
// saturation fixup
|
769 |
+
if ((bits & 0x7FU) > 0x7CU) {
|
770 |
+
// NaN
|
771 |
+
i = 0;
|
772 |
+
} else if (f > static_cast<float>(max_val)) {
|
773 |
+
// saturate maximum
|
774 |
+
i = max_val;
|
775 |
+
} else if (f < static_cast<float>(min_val)) {
|
776 |
+
// saturate minimum
|
777 |
+
i = min_val;
|
778 |
+
} else {
|
779 |
+
// normal value
|
780 |
+
i = static_cast<signed char>(f);
|
781 |
+
}
|
782 |
+
return i;
|
783 |
+
}
|
784 |
+
/**
|
785 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
786 |
+
* Conversion operator to \p short \p int data type.
|
787 |
+
* Clamps too large inputs to the output range.
|
788 |
+
* \p NaN inputs convert to \p zero.
|
789 |
+
*/
|
790 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator short int() const {
|
791 |
+
return __half2short_rz(__half(*this));
|
792 |
+
}
|
793 |
+
/**
|
794 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
795 |
+
* Conversion operator to \p int data type.
|
796 |
+
* Clamps too large inputs to the output range.
|
797 |
+
* \p NaN inputs convert to \p zero.
|
798 |
+
*/
|
799 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator int() const {
|
800 |
+
return __half2int_rz(__half(*this));
|
801 |
+
}
|
802 |
+
/**
|
803 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
804 |
+
* Conversion operator to \p long \p long \p int data type.
|
805 |
+
* Clamps too large inputs to the output range.
|
806 |
+
* \p NaN inputs convert to \p 0x8000000000000000LL.
|
807 |
+
*/
|
808 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator long long int() const {
|
809 |
+
return __half2ll_rz(__half(*this));
|
810 |
+
}
|
811 |
+
|
812 |
+
/**
|
813 |
+
* \ingroup CUDA_MATH_FP8_E5M2_STRUCT
|
814 |
+
* Conversion operator to \p bool data type.
|
815 |
+
* +0 and -0 inputs convert to \p false.
|
816 |
+
* Non-zero inputs convert to \p true.
|
817 |
+
*/
|
818 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator bool() const {
|
819 |
+
return (__x & 0x7FU) != 0U;
|
820 |
+
}
|
821 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
|
822 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
|
823 |
+
};
|
824 |
+
|
825 |
+
/**
|
826 |
+
* \defgroup CUDA_MATH_FP8X2_E5M2_STRUCT C++ struct for handling vector type of two fp8 values of e5m2 kind.
|
827 |
+
* \ingroup CUDA_MATH_INTRINSIC_FP8
|
828 |
+
*/
|
829 |
+
|
830 |
+
/**
|
831 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
832 |
+
* \brief __nv_fp8x2_e5m2 datatype
|
833 |
+
*
|
834 |
+
* \details This structure implements the datatype for handling two
|
835 |
+
* \p fp8 floating-point numbers of \p e5m2 kind each:
|
836 |
+
* with 1 sign, 5 exponent, 1 implicit and 2 explicit mantissa bits.
|
837 |
+
*
|
838 |
+
* The structure implements converting constructors and operators.
|
839 |
+
*/
|
840 |
+
struct __CUDA_ALIGN__(2) __nv_fp8x2_e5m2 {
|
841 |
+
public:
|
842 |
+
/**
|
843 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
844 |
+
* Storage variable contains the vector of two \p fp8 floating-point data
|
845 |
+
* values.
|
846 |
+
*/
|
847 |
+
__nv_fp8x2_storage_t __x;
|
848 |
+
|
849 |
+
/**
|
850 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
851 |
+
* Constructor by default.
|
852 |
+
*/
|
853 |
+
#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
|
854 |
+
__nv_fp8x2_e5m2() = default;
|
855 |
+
#else
|
856 |
+
__CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2() {}
|
857 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
858 |
+
|
859 |
+
#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
|
860 |
+
|
861 |
+
/* Construct from wider types */
|
862 |
+
|
863 |
+
/**
|
864 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
865 |
+
* Constructor from \p __half2 data type, relies on \p __NV_SATFINITE
|
866 |
+
* behavior for out-of-range values.
|
867 |
+
*/
|
868 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const __half2 f) {
|
869 |
+
__x = __nv_cvt_halfraw2_to_fp8x2(static_cast<__half2_raw>(f),
|
870 |
+
__NV_SATFINITE, __NV_E5M2);
|
871 |
+
}
|
872 |
+
/**
|
873 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
874 |
+
* Constructor from \p __nv_bfloat162 data type, relies on \p __NV_SATFINITE
|
875 |
+
* behavior for out-of-range values.
|
876 |
+
*/
|
877 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const __nv_bfloat162 f) {
|
878 |
+
__x = __nv_cvt_bfloat16raw2_to_fp8x2(static_cast<__nv_bfloat162_raw>(f),
|
879 |
+
__NV_SATFINITE, __NV_E5M2);
|
880 |
+
}
|
881 |
+
/**
|
882 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
883 |
+
* Constructor from \p float2 data type, relies on \p __NV_SATFINITE
|
884 |
+
* behavior for out-of-range values.
|
885 |
+
*/
|
886 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const float2 f) {
|
887 |
+
__x = __nv_cvt_float2_to_fp8x2(f, __NV_SATFINITE, __NV_E5M2);
|
888 |
+
}
|
889 |
+
/**
|
890 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
891 |
+
* Constructor from \p double2 data type, relies on \p __NV_SATFINITE
|
892 |
+
* behavior for out-of-range values.
|
893 |
+
*/
|
894 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e5m2(const double2 f) {
|
895 |
+
__x = __nv_cvt_double2_to_fp8x2(f, __NV_SATFINITE, __NV_E5M2);
|
896 |
+
}
|
897 |
+
|
898 |
+
#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
|
899 |
+
/* Widening converts */
|
900 |
+
/**
|
901 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
902 |
+
* Conversion operator to \p __half2 data type.
|
903 |
+
*/
|
904 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator __half2() const {
|
905 |
+
return static_cast<__half2>(__nv_cvt_fp8x2_to_halfraw2(__x, __NV_E5M2));
|
906 |
+
}
|
907 |
+
/**
|
908 |
+
* \ingroup CUDA_MATH_FP8X2_E5M2_STRUCT
|
909 |
+
* Conversion operator to \p float2 data type.
|
910 |
+
*/
|
911 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator float2() const {
|
912 |
+
return __internal_halfraw2_to_float2(
|
913 |
+
__nv_cvt_fp8x2_to_halfraw2(__x, __NV_E5M2));
|
914 |
+
}
|
915 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
|
916 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
|
917 |
+
};
|
918 |
+
|
919 |
+
__CUDA_HOSTDEVICE_FP8_DECL__ unsigned int
|
920 |
+
__internal_pack_u16x2_to_u32(const unsigned short int src_lo,
|
921 |
+
const unsigned short int src_hi) {
|
922 |
+
unsigned int dst;
|
923 |
+
#if (defined __CUDACC__) && (defined __CUDA_ARCH__)
|
924 |
+
asm("{ mov.b32 %0, {%1,%2};}\n" : "=r"(dst) : "h"(src_lo), "h"(src_hi));
|
925 |
+
#else
|
926 |
+
dst = (static_cast<unsigned int>(src_hi) << 16U) |
|
927 |
+
static_cast<unsigned int>(src_lo);
|
928 |
+
#endif
|
929 |
+
return dst;
|
930 |
+
}
|
931 |
+
|
932 |
+
/**
|
933 |
+
* \defgroup CUDA_MATH_FP8X4_E5M2_STRUCT C++ struct for handling vector type of four fp8 values of e5m2 kind.
|
934 |
+
* \ingroup CUDA_MATH_INTRINSIC_FP8
|
935 |
+
*/
|
936 |
+
|
937 |
+
/**
|
938 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
939 |
+
* \brief __nv_fp8x4_e5m2 datatype
|
940 |
+
*
|
941 |
+
* \details This structure implements the datatype for handling four
|
942 |
+
* \p fp8 floating-point numbers of \p e5m2 kind each:
|
943 |
+
* with 1 sign, 5 exponent, 1 implicit and 2 explicit mantissa bits.
|
944 |
+
*
|
945 |
+
* The structure implements converting constructors and operators.
|
946 |
+
*/
|
947 |
+
struct __CUDA_ALIGN__(4) __nv_fp8x4_e5m2 {
|
948 |
+
public:
|
949 |
+
/**
|
950 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
951 |
+
* Storage variable contains the vector of four \p fp8 floating-point data
|
952 |
+
* values.
|
953 |
+
*/
|
954 |
+
__nv_fp8x4_storage_t __x;
|
955 |
+
|
956 |
+
/**
|
957 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
958 |
+
* Constructor by default.
|
959 |
+
*/
|
960 |
+
#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
|
961 |
+
__nv_fp8x4_e5m2() = default;
|
962 |
+
#else
|
963 |
+
__CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2() {}
|
964 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
965 |
+
|
966 |
+
#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
|
967 |
+
|
968 |
+
/* Construct from wider types */
|
969 |
+
|
970 |
+
/**
|
971 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
972 |
+
* Constructor from a pair of \p __half2 data type values,
|
973 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
974 |
+
*/
|
975 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const __half2 flo,
|
976 |
+
const __half2 fhi) {
|
977 |
+
const __nv_fp8x2_storage_t rlo = __nv_cvt_halfraw2_to_fp8x2(
|
978 |
+
static_cast<__half2_raw>(flo), __NV_SATFINITE, __NV_E5M2);
|
979 |
+
const __nv_fp8x2_storage_t rhi = __nv_cvt_halfraw2_to_fp8x2(
|
980 |
+
static_cast<__half2_raw>(fhi), __NV_SATFINITE, __NV_E5M2);
|
981 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
982 |
+
}
|
983 |
+
/**
|
984 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
985 |
+
* Constructor from a pair of \p __nv_bfloat162 data type values,
|
986 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
987 |
+
*/
|
988 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const __nv_bfloat162 flo,
|
989 |
+
const __nv_bfloat162 fhi) {
|
990 |
+
const __nv_fp8x2_storage_t rlo = __nv_cvt_bfloat16raw2_to_fp8x2(
|
991 |
+
static_cast<__nv_bfloat162_raw>(flo), __NV_SATFINITE, __NV_E5M2);
|
992 |
+
const __nv_fp8x2_storage_t rhi = __nv_cvt_bfloat16raw2_to_fp8x2(
|
993 |
+
static_cast<__nv_bfloat162_raw>(fhi), __NV_SATFINITE, __NV_E5M2);
|
994 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
995 |
+
}
|
996 |
+
/**
|
997 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
998 |
+
* Constructor from \p float4 vector data type,
|
999 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
1000 |
+
*/
|
1001 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const float4 f) {
|
1002 |
+
const float2 flo = {f.x, f.y};
|
1003 |
+
const float2 fhi = {f.z, f.w};
|
1004 |
+
const __nv_fp8x2_storage_t rlo =
|
1005 |
+
__nv_cvt_float2_to_fp8x2(flo, __NV_SATFINITE, __NV_E5M2);
|
1006 |
+
const __nv_fp8x2_storage_t rhi =
|
1007 |
+
__nv_cvt_float2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E5M2);
|
1008 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
1009 |
+
}
|
1010 |
+
/**
|
1011 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
1012 |
+
* Constructor from \p double4 vector data type,
|
1013 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
1014 |
+
*/
|
1015 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e5m2(const double4 f) {
|
1016 |
+
const double2 flo = {f.x, f.y};
|
1017 |
+
const double2 fhi = {f.z, f.w};
|
1018 |
+
const __nv_fp8x2_storage_t rlo =
|
1019 |
+
__nv_cvt_double2_to_fp8x2(flo, __NV_SATFINITE, __NV_E5M2);
|
1020 |
+
const __nv_fp8x2_storage_t rhi =
|
1021 |
+
__nv_cvt_double2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E5M2);
|
1022 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
1023 |
+
}
|
1024 |
+
|
1025 |
+
#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
|
1026 |
+
/* Widening converts */
|
1027 |
+
|
1028 |
+
/**
|
1029 |
+
* \ingroup CUDA_MATH_FP8X4_E5M2_STRUCT
|
1030 |
+
* Conversion operator to \p float4 vector data type.
|
1031 |
+
*/
|
1032 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator float4() const {
|
1033 |
+
const __nv_fp8x2_storage_t slo = static_cast<__nv_fp8x2_storage_t>(__x);
|
1034 |
+
const __nv_fp8x2_storage_t shi =
|
1035 |
+
static_cast<__nv_fp8x2_storage_t>(__x >> 16U);
|
1036 |
+
float2 rlo = __internal_halfraw2_to_float2(
|
1037 |
+
__nv_cvt_fp8x2_to_halfraw2(slo, __NV_E5M2));
|
1038 |
+
float2 rhi = __internal_halfraw2_to_float2(
|
1039 |
+
__nv_cvt_fp8x2_to_halfraw2(shi, __NV_E5M2));
|
1040 |
+
float4 res = {rlo.x, rlo.y, rhi.x, rhi.y};
|
1041 |
+
return res;
|
1042 |
+
}
|
1043 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
|
1044 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
|
1045 |
+
};
|
1046 |
+
|
1047 |
+
/**
|
1048 |
+
* \defgroup CUDA_MATH_FP8_E4M3_STRUCT C++ struct for handling fp8 data type of e4m3 kind.
|
1049 |
+
* \ingroup CUDA_MATH_INTRINSIC_FP8
|
1050 |
+
*/
|
1051 |
+
|
1052 |
+
/**
|
1053 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1054 |
+
* \brief __nv_fp8_e4m3 datatype
|
1055 |
+
*
|
1056 |
+
* \details This structure implements the datatype for storing
|
1057 |
+
* \p fp8 floating-point numbers of \p e4m3 kind:
|
1058 |
+
* with 1 sign, 4 exponent, 1 implicit and 3 explicit mantissa bits.
|
1059 |
+
* The encoding doesn't support Infinity.
|
1060 |
+
* NaNs are limited to 0x7F and 0xFF values.
|
1061 |
+
*
|
1062 |
+
* The structure implements converting constructors and operators.
|
1063 |
+
*/
|
1064 |
+
struct __CUDA_ALIGN__(1) __nv_fp8_e4m3 {
|
1065 |
+
public:
|
1066 |
+
/**
|
1067 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1068 |
+
* Storage variable contains the \p fp8 floating-point data.
|
1069 |
+
*/
|
1070 |
+
__nv_fp8_storage_t __x;
|
1071 |
+
|
1072 |
+
/**
|
1073 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1074 |
+
* Constructor by default.
|
1075 |
+
*/
|
1076 |
+
#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
|
1077 |
+
__nv_fp8_e4m3() = default;
|
1078 |
+
#else
|
1079 |
+
__CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3() {}
|
1080 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
1081 |
+
|
1082 |
+
#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
|
1083 |
+
|
1084 |
+
/* Construct from wider FP types */
|
1085 |
+
/* Note we do avoid constructor init-list because of special host/device
|
1086 |
+
* compilation rules */
|
1087 |
+
|
1088 |
+
/**
|
1089 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1090 |
+
* Constructor from \p __half data type, relies on \p __NV_SATFINITE
|
1091 |
+
* behavior for out-of-range values.
|
1092 |
+
*/
|
1093 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const __half f) {
|
1094 |
+
__x = __nv_cvt_halfraw_to_fp8(static_cast<__half_raw>(f),
|
1095 |
+
__NV_SATFINITE, __NV_E4M3);
|
1096 |
+
}
|
1097 |
+
/**
|
1098 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1099 |
+
* Constructor from \p __nv_bfloat16 data type, relies on \p __NV_SATFINITE
|
1100 |
+
* behavior for out-of-range values.
|
1101 |
+
*/
|
1102 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const __nv_bfloat16 f) {
|
1103 |
+
__x = __nv_cvt_bfloat16raw_to_fp8(static_cast<__nv_bfloat16_raw>(f),
|
1104 |
+
__NV_SATFINITE, __NV_E4M3);
|
1105 |
+
}
|
1106 |
+
/**
|
1107 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1108 |
+
* Constructor from \p float data type, relies on \p __NV_SATFINITE behavior
|
1109 |
+
* for out-of-range values.
|
1110 |
+
*/
|
1111 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const float f) {
|
1112 |
+
__x = __nv_cvt_float_to_fp8(f, __NV_SATFINITE, __NV_E4M3);
|
1113 |
+
}
|
1114 |
+
/**
|
1115 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1116 |
+
* Constructor from \p double data type, relies on \p __NV_SATFINITE
|
1117 |
+
* behavior for out-of-range values.
|
1118 |
+
*/
|
1119 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const double f) {
|
1120 |
+
__x = __nv_cvt_double_to_fp8(f, __NV_SATFINITE, __NV_E4M3);
|
1121 |
+
}
|
1122 |
+
|
1123 |
+
/* Converts from integral */
|
1124 |
+
|
1125 |
+
/**
|
1126 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1127 |
+
* Constructor from \p unsigned \p short \p int data type, relies on \p
|
1128 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
1129 |
+
*/
|
1130 |
+
explicit __CUDA_HOSTDEVICE_FP8__
|
1131 |
+
__nv_fp8_e4m3(const unsigned short int val) {
|
1132 |
+
__x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
|
1133 |
+
}
|
1134 |
+
/**
|
1135 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1136 |
+
* Constructor from \p unsigned \p int data type, relies on \p
|
1137 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
1138 |
+
*/
|
1139 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const unsigned int val) {
|
1140 |
+
__x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
|
1141 |
+
}
|
1142 |
+
/**
|
1143 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1144 |
+
* Constructor from \p unsigned \p long \p long \p int data type, relies on
|
1145 |
+
* \p __NV_SATFINITE behavior for out-of-range values.
|
1146 |
+
*/
|
1147 |
+
explicit __CUDA_HOSTDEVICE_FP8__
|
1148 |
+
__nv_fp8_e4m3(const unsigned long long int val) {
|
1149 |
+
__x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
|
1150 |
+
}
|
1151 |
+
|
1152 |
+
/**
|
1153 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1154 |
+
* Constructor from \p short \p int data type, relies on \p
|
1155 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
1156 |
+
*/
|
1157 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const short int val) {
|
1158 |
+
__x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
|
1159 |
+
}
|
1160 |
+
/**
|
1161 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1162 |
+
* Constructor from \p int data type, relies on \p __NV_SATFINITE behavior
|
1163 |
+
* for out-of-range values.
|
1164 |
+
*/
|
1165 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const int val) {
|
1166 |
+
__x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
|
1167 |
+
}
|
1168 |
+
/**
|
1169 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1170 |
+
* Constructor from \p long \p long \p int data type, relies on \p
|
1171 |
+
* __NV_SATFINITE behavior for out-of-range values.
|
1172 |
+
*/
|
1173 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8_e4m3(const long long int val) {
|
1174 |
+
__x = static_cast<__nv_fp8_e4m3>(static_cast<float>(val)).__x;
|
1175 |
+
}
|
1176 |
+
|
1177 |
+
#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
|
1178 |
+
/* Widening FP converts */
|
1179 |
+
/**
|
1180 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1181 |
+
* Conversion operator to \p __half data type.
|
1182 |
+
*/
|
1183 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator __half() const {
|
1184 |
+
return static_cast<__half>(__nv_cvt_fp8_to_halfraw(__x, __NV_E4M3));
|
1185 |
+
}
|
1186 |
+
/**
|
1187 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1188 |
+
* Conversion operator to \p float data type.
|
1189 |
+
*/
|
1190 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator float() const {
|
1191 |
+
return __internal_halfraw_to_float(
|
1192 |
+
__nv_cvt_fp8_to_halfraw(__x, __NV_E4M3));
|
1193 |
+
}
|
1194 |
+
/**
|
1195 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1196 |
+
* Conversion operator to \p __nv_bfloat16 data type.
|
1197 |
+
*/
|
1198 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator __nv_bfloat16() const {
|
1199 |
+
return static_cast<__nv_bfloat16>(
|
1200 |
+
__internal_float_to_bf16raw_rz(float(*this)));
|
1201 |
+
}
|
1202 |
+
/**
|
1203 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1204 |
+
* Conversion operator to \p double data type.
|
1205 |
+
*/
|
1206 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator double() const {
|
1207 |
+
return static_cast<double>(float(*this));
|
1208 |
+
}
|
1209 |
+
|
1210 |
+
/* Convert to integral */
|
1211 |
+
|
1212 |
+
/**
|
1213 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1214 |
+
* Conversion operator to \p unsigned \p char data type.
|
1215 |
+
* Clamps negative and too large inputs to the output range.
|
1216 |
+
* \p NaN inputs convert to \p zero.
|
1217 |
+
*/
|
1218 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned char() const {
|
1219 |
+
unsigned char i;
|
1220 |
+
const float f = float(*this);
|
1221 |
+
const unsigned char max_val = 0xFFU;
|
1222 |
+
const unsigned char min_val = 0U;
|
1223 |
+
const unsigned char bits = (*this).__x;
|
1224 |
+
// saturation fixup
|
1225 |
+
if ((bits & 0x7FU) == 0x7FU) {
|
1226 |
+
// NaN
|
1227 |
+
i = 0;
|
1228 |
+
} else if (f > static_cast<float>(max_val)) {
|
1229 |
+
// saturate maximum
|
1230 |
+
i = max_val;
|
1231 |
+
} else if (f < static_cast<float>(min_val)) {
|
1232 |
+
// saturate minimum
|
1233 |
+
i = min_val;
|
1234 |
+
} else {
|
1235 |
+
// normal value
|
1236 |
+
i = static_cast<unsigned char>(f);
|
1237 |
+
}
|
1238 |
+
return i;
|
1239 |
+
}
|
1240 |
+
|
1241 |
+
/**
|
1242 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1243 |
+
* Conversion operator to \p unsigned \p short \p int data type.
|
1244 |
+
* Clamps negative inputs to zero.
|
1245 |
+
* \p NaN inputs convert to \p zero.
|
1246 |
+
*/
|
1247 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned short int() const {
|
1248 |
+
return __half2ushort_rz(__half(*this));
|
1249 |
+
}
|
1250 |
+
/**
|
1251 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1252 |
+
* Conversion operator to \p unsigned \p int data type.
|
1253 |
+
* Clamps negative inputs to zero.
|
1254 |
+
* \p NaN inputs convert to \p zero.
|
1255 |
+
*/
|
1256 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned int() const {
|
1257 |
+
return __half2uint_rz(__half(*this));
|
1258 |
+
}
|
1259 |
+
/**
|
1260 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1261 |
+
* Conversion operator to \p unsigned \p long \p long \p int data type.
|
1262 |
+
* Clamps negative inputs to zero.
|
1263 |
+
* \p NaN inputs convert to \p 0x8000000000000000ULL.
|
1264 |
+
*/
|
1265 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator unsigned long long int() const {
|
1266 |
+
return __half2ull_rz(__half(*this));
|
1267 |
+
}
|
1268 |
+
|
1269 |
+
/**
|
1270 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1271 |
+
* Conversion operator to \p signed \p char data type.
|
1272 |
+
* Clamps too large inputs to the output range.
|
1273 |
+
* \p NaN inputs convert to \p zero.
|
1274 |
+
*/
|
1275 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator signed char() const {
|
1276 |
+
signed char i;
|
1277 |
+
const float f = float(*this);
|
1278 |
+
const signed char max_val = (signed char)0x7FU;
|
1279 |
+
const signed char min_val = (signed char)0x80U;
|
1280 |
+
const unsigned char bits = (*this).__x;
|
1281 |
+
// saturation fixup
|
1282 |
+
if ((bits & 0x7FU) == 0x7FU) {
|
1283 |
+
// NaN
|
1284 |
+
i = 0;
|
1285 |
+
} else if (f > static_cast<float>(max_val)) {
|
1286 |
+
// saturate maximum
|
1287 |
+
i = max_val;
|
1288 |
+
} else if (f < static_cast<float>(min_val)) {
|
1289 |
+
// saturate minimum
|
1290 |
+
i = min_val;
|
1291 |
+
} else {
|
1292 |
+
// normal value
|
1293 |
+
i = static_cast<signed char>(f);
|
1294 |
+
}
|
1295 |
+
return i;
|
1296 |
+
}
|
1297 |
+
/**
|
1298 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1299 |
+
* Conversion operator to \p short \p int data type.
|
1300 |
+
* \p NaN inputs convert to \p zero.
|
1301 |
+
*/
|
1302 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator short int() const {
|
1303 |
+
return __half2short_rz(__half(*this));
|
1304 |
+
}
|
1305 |
+
/**
|
1306 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1307 |
+
* Conversion operator to \p int data type.
|
1308 |
+
* \p NaN inputs convert to \p zero.
|
1309 |
+
*/
|
1310 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator int() const {
|
1311 |
+
return __half2int_rz(__half(*this));
|
1312 |
+
}
|
1313 |
+
/**
|
1314 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1315 |
+
* Conversion operator to \p long \p long \p int data type.
|
1316 |
+
* \p NaN inputs convert to \p 0x8000000000000000LL.
|
1317 |
+
*/
|
1318 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator long long int() const {
|
1319 |
+
return __half2ll_rz(__half(*this));
|
1320 |
+
}
|
1321 |
+
|
1322 |
+
/**
|
1323 |
+
* \ingroup CUDA_MATH_FP8_E4M3_STRUCT
|
1324 |
+
* Conversion operator to \p bool data type.
|
1325 |
+
* +0 and -0 inputs convert to \p false.
|
1326 |
+
* Non-zero inputs convert to \p true.
|
1327 |
+
*/
|
1328 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator bool() const {
|
1329 |
+
return (__x & 0x7FU) != 0U;
|
1330 |
+
}
|
1331 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
|
1332 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
|
1333 |
+
};
|
1334 |
+
|
1335 |
+
/**
|
1336 |
+
* \defgroup CUDA_MATH_FP8X2_E4M3_STRUCT C++ struct for handling vector type of two fp8 values of e4m3 kind.
|
1337 |
+
* \ingroup CUDA_MATH_INTRINSIC_FP8
|
1338 |
+
*/
|
1339 |
+
|
1340 |
+
/**
|
1341 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1342 |
+
* \brief __nv_fp8x2_e4m3 datatype
|
1343 |
+
*
|
1344 |
+
* \details This structure implements the datatype for storage
|
1345 |
+
* and operations on the vector of two \p fp8 values of \p e4m3 kind each:
|
1346 |
+
* with 1 sign, 4 exponent, 1 implicit and 3 explicit mantissa bits.
|
1347 |
+
* The encoding doesn't support Infinity.
|
1348 |
+
* NaNs are limited to 0x7F and 0xFF values.
|
1349 |
+
*/
|
1350 |
+
struct __CUDA_ALIGN__(2) __nv_fp8x2_e4m3 {
|
1351 |
+
public:
|
1352 |
+
/**
|
1353 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1354 |
+
* Storage variable contains the vector of two \p fp8 floating-point data
|
1355 |
+
* values.
|
1356 |
+
*/
|
1357 |
+
__nv_fp8x2_storage_t __x;
|
1358 |
+
|
1359 |
+
/**
|
1360 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1361 |
+
* Constructor by default.
|
1362 |
+
*/
|
1363 |
+
#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
|
1364 |
+
__nv_fp8x2_e4m3() = default;
|
1365 |
+
#else
|
1366 |
+
__CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3() {}
|
1367 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
1368 |
+
|
1369 |
+
#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
|
1370 |
+
|
1371 |
+
/* Construct from wider types */
|
1372 |
+
|
1373 |
+
/**
|
1374 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1375 |
+
* Constructor from \p __half2 data type, relies on \p __NV_SATFINITE
|
1376 |
+
* behavior for out-of-range values.
|
1377 |
+
*/
|
1378 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const __half2 f) {
|
1379 |
+
__x = __nv_cvt_halfraw2_to_fp8x2(static_cast<__half2_raw>(f),
|
1380 |
+
__NV_SATFINITE, __NV_E4M3);
|
1381 |
+
}
|
1382 |
+
/**
|
1383 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1384 |
+
* Constructor from \p __nv_bfloat162 data type, relies on \p __NV_SATFINITE
|
1385 |
+
* behavior for out-of-range values.
|
1386 |
+
*/
|
1387 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const __nv_bfloat162 f) {
|
1388 |
+
__x = __nv_cvt_bfloat16raw2_to_fp8x2(static_cast<__nv_bfloat162_raw>(f),
|
1389 |
+
__NV_SATFINITE, __NV_E4M3);
|
1390 |
+
}
|
1391 |
+
/**
|
1392 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1393 |
+
* Constructor from \p float2 data type, relies on \p __NV_SATFINITE
|
1394 |
+
* behavior for out-of-range values.
|
1395 |
+
*/
|
1396 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const float2 f) {
|
1397 |
+
__x = __nv_cvt_float2_to_fp8x2(f, __NV_SATFINITE, __NV_E4M3);
|
1398 |
+
}
|
1399 |
+
/**
|
1400 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1401 |
+
* Constructor from \p double2 data type, relies on \p __NV_SATFINITE
|
1402 |
+
* behavior for out-of-range values.
|
1403 |
+
*/
|
1404 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x2_e4m3(const double2 f) {
|
1405 |
+
__x = __nv_cvt_double2_to_fp8x2(f, __NV_SATFINITE, __NV_E4M3);
|
1406 |
+
}
|
1407 |
+
|
1408 |
+
#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
|
1409 |
+
/* Widening converts */
|
1410 |
+
/**
|
1411 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1412 |
+
* Conversion operator to \p __half2 data type.
|
1413 |
+
*/
|
1414 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator __half2() const {
|
1415 |
+
return static_cast<__half2>(__nv_cvt_fp8x2_to_halfraw2(__x, __NV_E4M3));
|
1416 |
+
}
|
1417 |
+
/**
|
1418 |
+
* \ingroup CUDA_MATH_FP8X2_E4M3_STRUCT
|
1419 |
+
* Conversion operator to \p float2 data type.
|
1420 |
+
*/
|
1421 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator float2() const {
|
1422 |
+
return __internal_halfraw2_to_float2(
|
1423 |
+
__nv_cvt_fp8x2_to_halfraw2(__x, __NV_E4M3));
|
1424 |
+
}
|
1425 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
|
1426 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
|
1427 |
+
};
|
1428 |
+
|
1429 |
+
/**
|
1430 |
+
* \defgroup CUDA_MATH_FP8X4_E4M3_STRUCT C++ struct for handling vector type of four fp8 values of e4m3 kind.
|
1431 |
+
* \ingroup CUDA_MATH_INTRINSIC_FP8
|
1432 |
+
*/
|
1433 |
+
|
1434 |
+
/**
|
1435 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1436 |
+
* \brief __nv_fp8x4_e4m3 datatype
|
1437 |
+
*
|
1438 |
+
* \details This structure implements the datatype for storage
|
1439 |
+
* and operations on the vector of four \p fp8 values of \p e4m3 kind each:
|
1440 |
+
* with 1 sign, 4 exponent, 1 implicit and 3 explicit mantissa bits.
|
1441 |
+
* The encoding doesn't support Infinity.
|
1442 |
+
* NaNs are limited to 0x7F and 0xFF values.
|
1443 |
+
*/
|
1444 |
+
struct __CUDA_ALIGN__(4) __nv_fp8x4_e4m3 {
|
1445 |
+
public:
|
1446 |
+
/**
|
1447 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1448 |
+
* Storage variable contains the vector of four \p fp8 floating-point data
|
1449 |
+
* values.
|
1450 |
+
*/
|
1451 |
+
__nv_fp8x4_storage_t __x;
|
1452 |
+
|
1453 |
+
/**
|
1454 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1455 |
+
* Constructor by default.
|
1456 |
+
*/
|
1457 |
+
#if defined(__CPP_VERSION_AT_LEAST_11_FP8)
|
1458 |
+
__nv_fp8x4_e4m3() = default;
|
1459 |
+
#else
|
1460 |
+
__CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3() {}
|
1461 |
+
#endif /* defined(__CPP_VERSION_AT_LEAST_11_FP8) */
|
1462 |
+
|
1463 |
+
#if !defined(__CUDA_NO_FP8_CONVERSIONS__)
|
1464 |
+
|
1465 |
+
/* Construct from wider types */
|
1466 |
+
|
1467 |
+
/**
|
1468 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1469 |
+
* Constructor from a pair of \p __half2 data type values,
|
1470 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
1471 |
+
*/
|
1472 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const __half2 flo,
|
1473 |
+
const __half2 fhi) {
|
1474 |
+
const __nv_fp8x2_storage_t rlo = __nv_cvt_halfraw2_to_fp8x2(
|
1475 |
+
static_cast<__half2_raw>(flo), __NV_SATFINITE, __NV_E4M3);
|
1476 |
+
const __nv_fp8x2_storage_t rhi = __nv_cvt_halfraw2_to_fp8x2(
|
1477 |
+
static_cast<__half2_raw>(fhi), __NV_SATFINITE, __NV_E4M3);
|
1478 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
1479 |
+
}
|
1480 |
+
/**
|
1481 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1482 |
+
* Constructor from a pair of \p __nv_bfloat162 data type values,
|
1483 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
1484 |
+
*/
|
1485 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const __nv_bfloat162 flo,
|
1486 |
+
const __nv_bfloat162 fhi) {
|
1487 |
+
const __nv_fp8x2_storage_t rlo = __nv_cvt_bfloat16raw2_to_fp8x2(
|
1488 |
+
static_cast<__nv_bfloat162_raw>(flo), __NV_SATFINITE, __NV_E4M3);
|
1489 |
+
const __nv_fp8x2_storage_t rhi = __nv_cvt_bfloat16raw2_to_fp8x2(
|
1490 |
+
static_cast<__nv_bfloat162_raw>(fhi), __NV_SATFINITE, __NV_E4M3);
|
1491 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
1492 |
+
}
|
1493 |
+
/**
|
1494 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1495 |
+
* Constructor from \p float4 vector data type,
|
1496 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
1497 |
+
*/
|
1498 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const float4 f) {
|
1499 |
+
const float2 flo = {f.x, f.y};
|
1500 |
+
const float2 fhi = {f.z, f.w};
|
1501 |
+
const __nv_fp8x2_storage_t rlo =
|
1502 |
+
__nv_cvt_float2_to_fp8x2(flo, __NV_SATFINITE, __NV_E4M3);
|
1503 |
+
const __nv_fp8x2_storage_t rhi =
|
1504 |
+
__nv_cvt_float2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E4M3);
|
1505 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
1506 |
+
}
|
1507 |
+
/**
|
1508 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1509 |
+
* Constructor from \p double4 vector data type,
|
1510 |
+
* relies on \p __NV_SATFINITE behavior for out-of-range values.
|
1511 |
+
*/
|
1512 |
+
explicit __CUDA_HOSTDEVICE_FP8__ __nv_fp8x4_e4m3(const double4 f) {
|
1513 |
+
const double2 flo = {f.x, f.y};
|
1514 |
+
const double2 fhi = {f.z, f.w};
|
1515 |
+
const __nv_fp8x2_storage_t rlo =
|
1516 |
+
__nv_cvt_double2_to_fp8x2(flo, __NV_SATFINITE, __NV_E4M3);
|
1517 |
+
const __nv_fp8x2_storage_t rhi =
|
1518 |
+
__nv_cvt_double2_to_fp8x2(fhi, __NV_SATFINITE, __NV_E4M3);
|
1519 |
+
__x = __internal_pack_u16x2_to_u32(rlo, rhi);
|
1520 |
+
}
|
1521 |
+
|
1522 |
+
#if !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__)
|
1523 |
+
/* Widening converts */
|
1524 |
+
|
1525 |
+
/**
|
1526 |
+
* \ingroup CUDA_MATH_FP8X4_E4M3_STRUCT
|
1527 |
+
* Conversion operator to \p float4 vector data type.
|
1528 |
+
*/
|
1529 |
+
explicit __CUDA_HOSTDEVICE_FP8__ operator float4() const {
|
1530 |
+
const __nv_fp8x2_storage_t slo = static_cast<__nv_fp8x2_storage_t>(__x);
|
1531 |
+
const __nv_fp8x2_storage_t shi =
|
1532 |
+
static_cast<__nv_fp8x2_storage_t>(__x >> 16U);
|
1533 |
+
float2 rlo = __internal_halfraw2_to_float2(
|
1534 |
+
__nv_cvt_fp8x2_to_halfraw2(slo, __NV_E4M3));
|
1535 |
+
float2 rhi = __internal_halfraw2_to_float2(
|
1536 |
+
__nv_cvt_fp8x2_to_halfraw2(shi, __NV_E4M3));
|
1537 |
+
float4 res = {rlo.x, rlo.y, rhi.x, rhi.y};
|
1538 |
+
return res;
|
1539 |
+
}
|
1540 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSION_OPERATORS__) */
|
1541 |
+
#endif /* !defined(__CUDA_NO_FP8_CONVERSIONS__) */
|
1542 |
+
};
|
1543 |
+
|
1544 |
+
#endif /* defined(__cplusplus) */
|
1545 |
+
|
1546 |
+
#endif /* end of include guard: __CUDA_FP8_HPP__ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_gl_interop.h
ADDED
@@ -0,0 +1,514 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
1 |
+
/*
|
2 |
+
* Copyright 1993-2012 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__CUDA_GL_INTEROP_H__)
|
51 |
+
#define __CUDA_GL_INTEROP_H__
|
52 |
+
|
53 |
+
#include "cuda_runtime_api.h"
|
54 |
+
|
55 |
+
#if defined(__APPLE__)
|
56 |
+
|
57 |
+
#include <OpenGL/gl.h>
|
58 |
+
|
59 |
+
#else /* __APPLE__ */
|
60 |
+
|
61 |
+
#if defined(__arm__) || defined(__aarch64__)
|
62 |
+
#ifndef GL_VERSION
|
63 |
+
#error Please include the appropriate gl headers before including cuda_gl_interop.h
|
64 |
+
#endif
|
65 |
+
#else
|
66 |
+
#include <GL/gl.h>
|
67 |
+
#endif
|
68 |
+
|
69 |
+
#endif /* __APPLE__ */
|
70 |
+
|
71 |
+
/** \cond impl_private */
|
72 |
+
#if defined(__DOXYGEN_ONLY__) || defined(CUDA_ENABLE_DEPRECATED)
|
73 |
+
#define __CUDA_DEPRECATED
|
74 |
+
#elif defined(_MSC_VER)
|
75 |
+
#define __CUDA_DEPRECATED __declspec(deprecated)
|
76 |
+
#elif defined(__GNUC__)
|
77 |
+
#define __CUDA_DEPRECATED __attribute__((deprecated))
|
78 |
+
#else
|
79 |
+
#define __CUDA_DEPRECATED
|
80 |
+
#endif
|
81 |
+
/** \endcond impl_private */
|
82 |
+
|
83 |
+
#if defined(__cplusplus)
|
84 |
+
extern "C" {
|
85 |
+
#endif /* __cplusplus */
|
86 |
+
|
87 |
+
/**
|
88 |
+
* \addtogroup CUDART_OPENGL OpenGL Interoperability
|
89 |
+
* This section describes the OpenGL interoperability functions of the CUDA
|
90 |
+
* runtime application programming interface. Note that mapping of OpenGL
|
91 |
+
* resources is performed with the graphics API agnostic, resource mapping
|
92 |
+
* interface described in \ref CUDART_INTEROP "Graphics Interopability".
|
93 |
+
*
|
94 |
+
* @{
|
95 |
+
*/
|
96 |
+
|
97 |
+
/**
|
98 |
+
* CUDA devices corresponding to the current OpenGL context
|
99 |
+
*/
|
100 |
+
enum cudaGLDeviceList
|
101 |
+
{
|
102 |
+
cudaGLDeviceListAll = 1, /**< The CUDA devices for all GPUs used by the current OpenGL context */
|
103 |
+
cudaGLDeviceListCurrentFrame = 2, /**< The CUDA devices for the GPUs used by the current OpenGL context in its currently rendering frame */
|
104 |
+
cudaGLDeviceListNextFrame = 3 /**< The CUDA devices for the GPUs to be used by the current OpenGL context in the next frame */
|
105 |
+
};
|
106 |
+
|
107 |
+
/**
|
108 |
+
* \brief Gets the CUDA devices associated with the current OpenGL context
|
109 |
+
*
|
110 |
+
* Returns in \p *pCudaDeviceCount the number of CUDA-compatible devices
|
111 |
+
* corresponding to the current OpenGL context. Also returns in \p *pCudaDevices
|
112 |
+
* at most \p cudaDeviceCount of the CUDA-compatible devices corresponding to
|
113 |
+
* the current OpenGL context. If any of the GPUs being used by the current OpenGL
|
114 |
+
* context are not CUDA capable then the call will return ::cudaErrorNoDevice.
|
115 |
+
*
|
116 |
+
* \param pCudaDeviceCount - Returned number of CUDA devices corresponding to the
|
117 |
+
* current OpenGL context
|
118 |
+
* \param pCudaDevices - Returned CUDA devices corresponding to the current
|
119 |
+
* OpenGL context
|
120 |
+
* \param cudaDeviceCount - The size of the output device array \p pCudaDevices
|
121 |
+
* \param deviceList - The set of devices to return. This set may be
|
122 |
+
* ::cudaGLDeviceListAll for all devices,
|
123 |
+
* ::cudaGLDeviceListCurrentFrame for the devices used to
|
124 |
+
* render the current frame (in SLI), or
|
125 |
+
* ::cudaGLDeviceListNextFrame for the devices used to
|
126 |
+
* render the next frame (in SLI).
|
127 |
+
*
|
128 |
+
* \return
|
129 |
+
* ::cudaSuccess,
|
130 |
+
* ::cudaErrorNoDevice,
|
131 |
+
* ::cudaErrorInvalidGraphicsContext,
|
132 |
+
* ::cudaErrorOperatingSystem,
|
133 |
+
* ::cudaErrorUnknown
|
134 |
+
*
|
135 |
+
* \note This function is not supported on Mac OS X.
|
136 |
+
* \notefnerr
|
137 |
+
*
|
138 |
+
* \sa
|
139 |
+
* ::cudaGraphicsUnregisterResource,
|
140 |
+
* ::cudaGraphicsMapResources,
|
141 |
+
* ::cudaGraphicsSubResourceGetMappedArray,
|
142 |
+
* ::cudaGraphicsResourceGetMappedPointer,
|
143 |
+
* ::cuGLGetDevices
|
144 |
+
*/
|
145 |
+
extern __host__ cudaError_t CUDARTAPI cudaGLGetDevices(unsigned int *pCudaDeviceCount, int *pCudaDevices, unsigned int cudaDeviceCount, enum cudaGLDeviceList deviceList);
|
146 |
+
|
147 |
+
/**
|
148 |
+
* \brief Register an OpenGL texture or renderbuffer object
|
149 |
+
*
|
150 |
+
* Registers the texture or renderbuffer object specified by \p image for access by CUDA.
|
151 |
+
* A handle to the registered object is returned as \p resource.
|
152 |
+
*
|
153 |
+
* \p target must match the type of the object, and must be one of ::GL_TEXTURE_2D,
|
154 |
+
* ::GL_TEXTURE_RECTANGLE, ::GL_TEXTURE_CUBE_MAP, ::GL_TEXTURE_3D, ::GL_TEXTURE_2D_ARRAY,
|
155 |
+
* or ::GL_RENDERBUFFER.
|
156 |
+
*
|
157 |
+
* The register flags \p flags specify the intended usage, as follows:
|
158 |
+
* - ::cudaGraphicsRegisterFlagsNone: Specifies no hints about how this
|
159 |
+
* resource will be used. It is therefore assumed that this resource will be
|
160 |
+
* read from and written to by CUDA. This is the default value.
|
161 |
+
* - ::cudaGraphicsRegisterFlagsReadOnly: Specifies that CUDA
|
162 |
+
* will not write to this resource.
|
163 |
+
* - ::cudaGraphicsRegisterFlagsWriteDiscard: Specifies that
|
164 |
+
* CUDA will not read from this resource and will write over the
|
165 |
+
* entire contents of the resource, so none of the data previously
|
166 |
+
* stored in the resource will be preserved.
|
167 |
+
* - ::cudaGraphicsRegisterFlagsSurfaceLoadStore: Specifies that CUDA will
|
168 |
+
* bind this resource to a surface reference.
|
169 |
+
* - ::cudaGraphicsRegisterFlagsTextureGather: Specifies that CUDA will perform
|
170 |
+
* texture gather operations on this resource.
|
171 |
+
*
|
172 |
+
* The following image formats are supported. For brevity's sake, the list is abbreviated.
|
173 |
+
* For ex., {GL_R, GL_RG} X {8, 16} would expand to the following 4 formats
|
174 |
+
* {GL_R8, GL_R16, GL_RG8, GL_RG16} :
|
175 |
+
* - GL_RED, GL_RG, GL_RGBA, GL_LUMINANCE, GL_ALPHA, GL_LUMINANCE_ALPHA, GL_INTENSITY
|
176 |
+
* - {GL_R, GL_RG, GL_RGBA} X {8, 16, 16F, 32F, 8UI, 16UI, 32UI, 8I, 16I, 32I}
|
177 |
+
* - {GL_LUMINANCE, GL_ALPHA, GL_LUMINANCE_ALPHA, GL_INTENSITY} X
|
178 |
+
* {8, 16, 16F_ARB, 32F_ARB, 8UI_EXT, 16UI_EXT, 32UI_EXT, 8I_EXT, 16I_EXT, 32I_EXT}
|
179 |
+
*
|
180 |
+
* The following image classes are currently disallowed:
|
181 |
+
* - Textures with borders
|
182 |
+
* - Multisampled renderbuffers
|
183 |
+
*
|
184 |
+
* \param resource - Pointer to the returned object handle
|
185 |
+
* \param image - name of texture or renderbuffer object to be registered
|
186 |
+
* \param target - Identifies the type of object specified by \p image
|
187 |
+
* \param flags - Register flags
|
188 |
+
*
|
189 |
+
* \return
|
190 |
+
* ::cudaSuccess,
|
191 |
+
* ::cudaErrorInvalidDevice,
|
192 |
+
* ::cudaErrorInvalidValue,
|
193 |
+
* ::cudaErrorInvalidResourceHandle,
|
194 |
+
* ::cudaErrorOperatingSystem,
|
195 |
+
* ::cudaErrorUnknown
|
196 |
+
* \notefnerr
|
197 |
+
*
|
198 |
+
* \sa
|
199 |
+
* ::cudaGraphicsUnregisterResource,
|
200 |
+
* ::cudaGraphicsMapResources,
|
201 |
+
* ::cudaGraphicsSubResourceGetMappedArray,
|
202 |
+
* ::cuGraphicsGLRegisterImage
|
203 |
+
*/
|
204 |
+
extern __host__ cudaError_t CUDARTAPI cudaGraphicsGLRegisterImage(struct cudaGraphicsResource **resource, GLuint image, GLenum target, unsigned int flags);
|
205 |
+
|
206 |
+
/**
|
207 |
+
* \brief Registers an OpenGL buffer object
|
208 |
+
*
|
209 |
+
* Registers the buffer object specified by \p buffer for access by
|
210 |
+
* CUDA. A handle to the registered object is returned as \p
|
211 |
+
* resource. The register flags \p flags specify the intended usage,
|
212 |
+
* as follows:
|
213 |
+
*
|
214 |
+
* - ::cudaGraphicsRegisterFlagsNone: Specifies no hints about how this
|
215 |
+
* resource will be used. It is therefore assumed that this resource will be
|
216 |
+
* read from and written to by CUDA. This is the default value.
|
217 |
+
* - ::cudaGraphicsRegisterFlagsReadOnly: Specifies that CUDA
|
218 |
+
* will not write to this resource.
|
219 |
+
* - ::cudaGraphicsRegisterFlagsWriteDiscard: Specifies that
|
220 |
+
* CUDA will not read from this resource and will write over the
|
221 |
+
* entire contents of the resource, so none of the data previously
|
222 |
+
* stored in the resource will be preserved.
|
223 |
+
*
|
224 |
+
* \param resource - Pointer to the returned object handle
|
225 |
+
* \param buffer - name of buffer object to be registered
|
226 |
+
* \param flags - Register flags
|
227 |
+
*
|
228 |
+
* \return
|
229 |
+
* ::cudaSuccess,
|
230 |
+
* ::cudaErrorInvalidDevice,
|
231 |
+
* ::cudaErrorInvalidValue,
|
232 |
+
* ::cudaErrorInvalidResourceHandle,
|
233 |
+
* ::cudaErrorOperatingSystem,
|
234 |
+
* ::cudaErrorUnknown
|
235 |
+
* \notefnerr
|
236 |
+
*
|
237 |
+
* \sa
|
238 |
+
* ::cudaGraphicsUnregisterResource,
|
239 |
+
* ::cudaGraphicsMapResources,
|
240 |
+
* ::cudaGraphicsResourceGetMappedPointer,
|
241 |
+
* ::cuGraphicsGLRegisterBuffer
|
242 |
+
*/
|
243 |
+
extern __host__ cudaError_t CUDARTAPI cudaGraphicsGLRegisterBuffer(struct cudaGraphicsResource **resource, GLuint buffer, unsigned int flags);
|
244 |
+
|
245 |
+
#ifdef _WIN32
|
246 |
+
#ifndef WGL_NV_gpu_affinity
|
247 |
+
typedef void* HGPUNV;
|
248 |
+
#endif
|
249 |
+
|
250 |
+
/**
|
251 |
+
* \brief Gets the CUDA device associated with hGpu
|
252 |
+
*
|
253 |
+
* Returns the CUDA device associated with a hGpu, if applicable.
|
254 |
+
*
|
255 |
+
* \param device - Returns the device associated with hGpu, or -1 if hGpu is
|
256 |
+
* not a compute device.
|
257 |
+
* \param hGpu - Handle to a GPU, as queried via WGL_NV_gpu_affinity
|
258 |
+
*
|
259 |
+
* \return
|
260 |
+
* ::cudaSuccess
|
261 |
+
* \notefnerr
|
262 |
+
*
|
263 |
+
* \sa
|
264 |
+
* ::WGL_NV_gpu_affinity,
|
265 |
+
* ::cuWGLGetDevice
|
266 |
+
*/
|
267 |
+
extern __host__ cudaError_t CUDARTAPI cudaWGLGetDevice(int *device, HGPUNV hGpu);
|
268 |
+
#endif
|
269 |
+
|
270 |
+
/** @} */ /* END CUDART_OPENGL */
|
271 |
+
|
272 |
+
/**
|
273 |
+
* \addtogroup CUDART_OPENGL_DEPRECATED OpenGL Interoperability [DEPRECATED]
|
274 |
+
* This section describes deprecated OpenGL interoperability functionality.
|
275 |
+
*
|
276 |
+
* @{
|
277 |
+
*/
|
278 |
+
|
279 |
+
/**
|
280 |
+
* CUDA GL Map Flags
|
281 |
+
*/
|
282 |
+
enum cudaGLMapFlags
|
283 |
+
{
|
284 |
+
cudaGLMapFlagsNone = 0, /**< Default; Assume resource can be read/written */
|
285 |
+
cudaGLMapFlagsReadOnly = 1, /**< CUDA kernels will not write to this resource */
|
286 |
+
cudaGLMapFlagsWriteDiscard = 2 /**< CUDA kernels will only write to and will not read from this resource */
|
287 |
+
};
|
288 |
+
|
289 |
+
/**
|
290 |
+
* \brief Sets a CUDA device to use OpenGL interoperability
|
291 |
+
*
|
292 |
+
* \deprecated This function is deprecated as of CUDA 5.0.
|
293 |
+
*
|
294 |
+
* This function is deprecated and should no longer be used. It is
|
295 |
+
* no longer necessary to associate a CUDA device with an OpenGL
|
296 |
+
* context in order to achieve maximum interoperability performance.
|
297 |
+
*
|
298 |
+
* This function will immediately initialize the primary context on
|
299 |
+
* \p device if needed.
|
300 |
+
*
|
301 |
+
* \param device - Device to use for OpenGL interoperability
|
302 |
+
*
|
303 |
+
* \return
|
304 |
+
* ::cudaSuccess,
|
305 |
+
* ::cudaErrorInvalidDevice,
|
306 |
+
* ::cudaErrorSetOnActiveProcess
|
307 |
+
* \notefnerr
|
308 |
+
*
|
309 |
+
* \sa ::cudaGraphicsGLRegisterBuffer, ::cudaGraphicsGLRegisterImage
|
310 |
+
*/
|
311 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLSetGLDevice(int device);
|
312 |
+
|
313 |
+
/**
|
314 |
+
* \brief Registers a buffer object for access by CUDA
|
315 |
+
*
|
316 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
317 |
+
*
|
318 |
+
* Registers the buffer object of ID \p bufObj for access by
|
319 |
+
* CUDA. This function must be called before CUDA can map the buffer
|
320 |
+
* object. The OpenGL context used to create the buffer, or another
|
321 |
+
* context from the same share group, must be bound to the current
|
322 |
+
* thread when this is called.
|
323 |
+
*
|
324 |
+
* \param bufObj - Buffer object ID to register
|
325 |
+
*
|
326 |
+
* \return
|
327 |
+
* ::cudaSuccess,
|
328 |
+
* ::cudaErrorInitializationError
|
329 |
+
* \notefnerr
|
330 |
+
*
|
331 |
+
* \sa ::cudaGraphicsGLRegisterBuffer
|
332 |
+
*/
|
333 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLRegisterBufferObject(GLuint bufObj);
|
334 |
+
|
335 |
+
/**
|
336 |
+
* \brief Maps a buffer object for access by CUDA
|
337 |
+
*
|
338 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
339 |
+
*
|
340 |
+
* Maps the buffer object of ID \p bufObj into the address space of
|
341 |
+
* CUDA and returns in \p *devPtr the base pointer of the resulting
|
342 |
+
* mapping. The buffer must have previously been registered by
|
343 |
+
* calling ::cudaGLRegisterBufferObject(). While a buffer is mapped
|
344 |
+
* by CUDA, any OpenGL operation which references the buffer will
|
345 |
+
* result in undefined behavior. The OpenGL context used to create
|
346 |
+
* the buffer, or another context from the same share group, must be
|
347 |
+
* bound to the current thread when this is called.
|
348 |
+
*
|
349 |
+
* All streams in the current thread are synchronized with the current
|
350 |
+
* GL context.
|
351 |
+
*
|
352 |
+
* \param devPtr - Returned device pointer to CUDA object
|
353 |
+
* \param bufObj - Buffer object ID to map
|
354 |
+
*
|
355 |
+
* \return
|
356 |
+
* ::cudaSuccess,
|
357 |
+
* ::cudaErrorMapBufferObjectFailed
|
358 |
+
* \notefnerr
|
359 |
+
*
|
360 |
+
* \sa ::cudaGraphicsMapResources
|
361 |
+
*/
|
362 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLMapBufferObject(void **devPtr, GLuint bufObj);
|
363 |
+
|
364 |
+
/**
|
365 |
+
* \brief Unmaps a buffer object for access by CUDA
|
366 |
+
*
|
367 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
368 |
+
*
|
369 |
+
* Unmaps the buffer object of ID \p bufObj for access by CUDA. When
|
370 |
+
* a buffer is unmapped, the base address returned by
|
371 |
+
* ::cudaGLMapBufferObject() is invalid and subsequent references to
|
372 |
+
* the address result in undefined behavior. The OpenGL context used
|
373 |
+
* to create the buffer, or another context from the same share group,
|
374 |
+
* must be bound to the current thread when this is called.
|
375 |
+
*
|
376 |
+
* All streams in the current thread are synchronized with the current
|
377 |
+
* GL context.
|
378 |
+
*
|
379 |
+
* \param bufObj - Buffer object to unmap
|
380 |
+
*
|
381 |
+
* \return
|
382 |
+
* ::cudaSuccess,
|
383 |
+
* ::cudaErrorUnmapBufferObjectFailed
|
384 |
+
* \notefnerr
|
385 |
+
*
|
386 |
+
* \sa ::cudaGraphicsUnmapResources
|
387 |
+
*/
|
388 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLUnmapBufferObject(GLuint bufObj);
|
389 |
+
|
390 |
+
/**
|
391 |
+
* \brief Unregisters a buffer object for access by CUDA
|
392 |
+
*
|
393 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
394 |
+
*
|
395 |
+
* Unregisters the buffer object of ID \p bufObj for access by CUDA
|
396 |
+
* and releases any CUDA resources associated with the buffer. Once a
|
397 |
+
* buffer is unregistered, it may no longer be mapped by CUDA. The GL
|
398 |
+
* context used to create the buffer, or another context from the
|
399 |
+
* same share group, must be bound to the current thread when this is
|
400 |
+
* called.
|
401 |
+
*
|
402 |
+
* \param bufObj - Buffer object to unregister
|
403 |
+
*
|
404 |
+
* \return
|
405 |
+
* ::cudaSuccess
|
406 |
+
* \notefnerr
|
407 |
+
*
|
408 |
+
* \sa ::cudaGraphicsUnregisterResource
|
409 |
+
*/
|
410 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLUnregisterBufferObject(GLuint bufObj);
|
411 |
+
|
412 |
+
/**
|
413 |
+
* \brief Set usage flags for mapping an OpenGL buffer
|
414 |
+
*
|
415 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
416 |
+
*
|
417 |
+
* Set flags for mapping the OpenGL buffer \p bufObj
|
418 |
+
*
|
419 |
+
* Changes to flags will take effect the next time \p bufObj is mapped.
|
420 |
+
* The \p flags argument may be any of the following:
|
421 |
+
*
|
422 |
+
* - ::cudaGLMapFlagsNone: Specifies no hints about how this buffer will
|
423 |
+
* be used. It is therefore assumed that this buffer will be read from and
|
424 |
+
* written to by CUDA kernels. This is the default value.
|
425 |
+
* - ::cudaGLMapFlagsReadOnly: Specifies that CUDA kernels which access this
|
426 |
+
* buffer will not write to the buffer.
|
427 |
+
* - ::cudaGLMapFlagsWriteDiscard: Specifies that CUDA kernels which access
|
428 |
+
* this buffer will not read from the buffer and will write over the
|
429 |
+
* entire contents of the buffer, so none of the data previously stored in
|
430 |
+
* the buffer will be preserved.
|
431 |
+
*
|
432 |
+
* If \p bufObj has not been registered for use with CUDA, then
|
433 |
+
* ::cudaErrorInvalidResourceHandle is returned. If \p bufObj is presently
|
434 |
+
* mapped for access by CUDA, then ::cudaErrorUnknown is returned.
|
435 |
+
*
|
436 |
+
* \param bufObj - Registered buffer object to set flags for
|
437 |
+
* \param flags - Parameters for buffer mapping
|
438 |
+
*
|
439 |
+
* \return
|
440 |
+
* ::cudaSuccess,
|
441 |
+
* ::cudaErrorInvalidValue,
|
442 |
+
* ::cudaErrorInvalidResourceHandle,
|
443 |
+
* ::cudaErrorUnknown
|
444 |
+
* \notefnerr
|
445 |
+
*
|
446 |
+
* \sa ::cudaGraphicsResourceSetMapFlags
|
447 |
+
*/
|
448 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLSetBufferObjectMapFlags(GLuint bufObj, unsigned int flags);
|
449 |
+
|
450 |
+
/**
|
451 |
+
* \brief Maps a buffer object for access by CUDA
|
452 |
+
*
|
453 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
454 |
+
*
|
455 |
+
* Maps the buffer object of ID \p bufObj into the address space of
|
456 |
+
* CUDA and returns in \p *devPtr the base pointer of the resulting
|
457 |
+
* mapping. The buffer must have previously been registered by
|
458 |
+
* calling ::cudaGLRegisterBufferObject(). While a buffer is mapped
|
459 |
+
* by CUDA, any OpenGL operation which references the buffer will
|
460 |
+
* result in undefined behavior. The OpenGL context used to create
|
461 |
+
* the buffer, or another context from the same share group, must be
|
462 |
+
* bound to the current thread when this is called.
|
463 |
+
*
|
464 |
+
* Stream /p stream is synchronized with the current GL context.
|
465 |
+
*
|
466 |
+
* \param devPtr - Returned device pointer to CUDA object
|
467 |
+
* \param bufObj - Buffer object ID to map
|
468 |
+
* \param stream - Stream to synchronize
|
469 |
+
*
|
470 |
+
* \return
|
471 |
+
* ::cudaSuccess,
|
472 |
+
* ::cudaErrorMapBufferObjectFailed
|
473 |
+
* \notefnerr
|
474 |
+
*
|
475 |
+
* \sa ::cudaGraphicsMapResources
|
476 |
+
*/
|
477 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLMapBufferObjectAsync(void **devPtr, GLuint bufObj, cudaStream_t stream);
|
478 |
+
|
479 |
+
/**
|
480 |
+
* \brief Unmaps a buffer object for access by CUDA
|
481 |
+
*
|
482 |
+
* \deprecated This function is deprecated as of CUDA 3.0.
|
483 |
+
*
|
484 |
+
* Unmaps the buffer object of ID \p bufObj for access by CUDA. When
|
485 |
+
* a buffer is unmapped, the base address returned by
|
486 |
+
* ::cudaGLMapBufferObject() is invalid and subsequent references to
|
487 |
+
* the address result in undefined behavior. The OpenGL context used
|
488 |
+
* to create the buffer, or another context from the same share group,
|
489 |
+
* must be bound to the current thread when this is called.
|
490 |
+
*
|
491 |
+
* Stream /p stream is synchronized with the current GL context.
|
492 |
+
*
|
493 |
+
* \param bufObj - Buffer object to unmap
|
494 |
+
* \param stream - Stream to synchronize
|
495 |
+
*
|
496 |
+
* \return
|
497 |
+
* ::cudaSuccess,
|
498 |
+
* ::cudaErrorUnmapBufferObjectFailed
|
499 |
+
* \notefnerr
|
500 |
+
*
|
501 |
+
* \sa ::cudaGraphicsUnmapResources
|
502 |
+
*/
|
503 |
+
extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLUnmapBufferObjectAsync(GLuint bufObj, cudaStream_t stream);
|
504 |
+
|
505 |
+
/** @} */ /* END CUDART_OPENGL_DEPRECATED */
|
506 |
+
|
507 |
+
#if defined(__cplusplus)
|
508 |
+
}
|
509 |
+
#endif /* __cplusplus */
|
510 |
+
|
511 |
+
#undef __CUDA_DEPRECATED
|
512 |
+
|
513 |
+
#endif /* __CUDA_GL_INTEROP_H__ */
|
514 |
+
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/cuda_vdpau_interop.h
ADDED
@@ -0,0 +1,201 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2012 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__CUDA_VDPAU_INTEROP_H__)
|
51 |
+
#define __CUDA_VDPAU_INTEROP_H__
|
52 |
+
|
53 |
+
#include "cuda_runtime_api.h"
|
54 |
+
|
55 |
+
#include <vdpau/vdpau.h>
|
56 |
+
|
57 |
+
#if defined(__cplusplus)
|
58 |
+
extern "C" {
|
59 |
+
#endif /* __cplusplus */
|
60 |
+
|
61 |
+
/**
|
62 |
+
* \addtogroup CUDART_VDPAU VDPAU Interoperability
|
63 |
+
* This section describes the VDPAU interoperability functions of the CUDA
|
64 |
+
* runtime application programming interface.
|
65 |
+
*
|
66 |
+
* @{
|
67 |
+
*/
|
68 |
+
|
69 |
+
/**
|
70 |
+
* \brief Gets the CUDA device associated with a VdpDevice.
|
71 |
+
*
|
72 |
+
* Returns the CUDA device associated with a VdpDevice, if applicable.
|
73 |
+
*
|
74 |
+
* \param device - Returns the device associated with vdpDevice, or -1 if
|
75 |
+
* the device associated with vdpDevice is not a compute device.
|
76 |
+
* \param vdpDevice - A VdpDevice handle
|
77 |
+
* \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
|
78 |
+
*
|
79 |
+
* \return
|
80 |
+
* ::cudaSuccess
|
81 |
+
* \notefnerr
|
82 |
+
*
|
83 |
+
* \sa
|
84 |
+
* ::cudaVDPAUSetVDPAUDevice,
|
85 |
+
* ::cuVDPAUGetDevice
|
86 |
+
*/
|
87 |
+
extern __host__ cudaError_t CUDARTAPI cudaVDPAUGetDevice(int *device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
|
88 |
+
|
89 |
+
/**
|
90 |
+
* \brief Sets a CUDA device to use VDPAU interoperability
|
91 |
+
*
|
92 |
+
* Records \p vdpDevice as the VdpDevice for VDPAU interoperability
|
93 |
+
* with the CUDA device \p device and sets \p device as the current
|
94 |
+
* device for the calling host thread.
|
95 |
+
*
|
96 |
+
* This function will immediately initialize the primary context on
|
97 |
+
* \p device if needed.
|
98 |
+
*
|
99 |
+
* If \p device has already been initialized then this call will fail
|
100 |
+
* with the error ::cudaErrorSetOnActiveProcess. In this case it is
|
101 |
+
* necessary to reset \p device using ::cudaDeviceReset() before
|
102 |
+
* VDPAU interoperability on \p device may be enabled.
|
103 |
+
*
|
104 |
+
* \param device - Device to use for VDPAU interoperability
|
105 |
+
* \param vdpDevice - The VdpDevice to interoperate with
|
106 |
+
* \param vdpGetProcAddress - VDPAU's VdpGetProcAddress function pointer
|
107 |
+
*
|
108 |
+
* \return
|
109 |
+
* ::cudaSuccess,
|
110 |
+
* ::cudaErrorInvalidDevice,
|
111 |
+
* ::cudaErrorSetOnActiveProcess
|
112 |
+
* \notefnerr
|
113 |
+
*
|
114 |
+
* \sa ::cudaGraphicsVDPAURegisterVideoSurface,
|
115 |
+
* ::cudaGraphicsVDPAURegisterOutputSurface,
|
116 |
+
* ::cudaDeviceReset
|
117 |
+
*/
|
118 |
+
extern __host__ cudaError_t CUDARTAPI cudaVDPAUSetVDPAUDevice(int device, VdpDevice vdpDevice, VdpGetProcAddress *vdpGetProcAddress);
|
119 |
+
|
120 |
+
/**
|
121 |
+
* \brief Register a VdpVideoSurface object
|
122 |
+
*
|
123 |
+
* Registers the VdpVideoSurface specified by \p vdpSurface for access by CUDA.
|
124 |
+
* A handle to the registered object is returned as \p resource.
|
125 |
+
* The surface's intended usage is specified using \p flags, as follows:
|
126 |
+
*
|
127 |
+
* - ::cudaGraphicsMapFlagsNone: Specifies no hints about how this
|
128 |
+
* resource will be used. It is therefore assumed that this resource will be
|
129 |
+
* read from and written to by CUDA. This is the default value.
|
130 |
+
* - ::cudaGraphicsMapFlagsReadOnly: Specifies that CUDA
|
131 |
+
* will not write to this resource.
|
132 |
+
* - ::cudaGraphicsMapFlagsWriteDiscard: Specifies that
|
133 |
+
* CUDA will not read from this resource and will write over the
|
134 |
+
* entire contents of the resource, so none of the data previously
|
135 |
+
* stored in the resource will be preserved.
|
136 |
+
*
|
137 |
+
* \param resource - Pointer to the returned object handle
|
138 |
+
* \param vdpSurface - VDPAU object to be registered
|
139 |
+
* \param flags - Map flags
|
140 |
+
*
|
141 |
+
* \return
|
142 |
+
* ::cudaSuccess,
|
143 |
+
* ::cudaErrorInvalidDevice,
|
144 |
+
* ::cudaErrorInvalidValue,
|
145 |
+
* ::cudaErrorInvalidResourceHandle,
|
146 |
+
* ::cudaErrorUnknown
|
147 |
+
* \notefnerr
|
148 |
+
*
|
149 |
+
* \sa
|
150 |
+
* ::cudaVDPAUSetVDPAUDevice,
|
151 |
+
* ::cudaGraphicsUnregisterResource,
|
152 |
+
* ::cudaGraphicsSubResourceGetMappedArray,
|
153 |
+
* ::cuGraphicsVDPAURegisterVideoSurface
|
154 |
+
*/
|
155 |
+
extern __host__ cudaError_t CUDARTAPI cudaGraphicsVDPAURegisterVideoSurface(struct cudaGraphicsResource **resource, VdpVideoSurface vdpSurface, unsigned int flags);
|
156 |
+
|
157 |
+
/**
|
158 |
+
* \brief Register a VdpOutputSurface object
|
159 |
+
*
|
160 |
+
* Registers the VdpOutputSurface specified by \p vdpSurface for access by CUDA.
|
161 |
+
* A handle to the registered object is returned as \p resource.
|
162 |
+
* The surface's intended usage is specified using \p flags, as follows:
|
163 |
+
*
|
164 |
+
* - ::cudaGraphicsMapFlagsNone: Specifies no hints about how this
|
165 |
+
* resource will be used. It is therefore assumed that this resource will be
|
166 |
+
* read from and written to by CUDA. This is the default value.
|
167 |
+
* - ::cudaGraphicsMapFlagsReadOnly: Specifies that CUDA
|
168 |
+
* will not write to this resource.
|
169 |
+
* - ::cudaGraphicsMapFlagsWriteDiscard: Specifies that
|
170 |
+
* CUDA will not read from this resource and will write over the
|
171 |
+
* entire contents of the resource, so none of the data previously
|
172 |
+
* stored in the resource will be preserved.
|
173 |
+
*
|
174 |
+
* \param resource - Pointer to the returned object handle
|
175 |
+
* \param vdpSurface - VDPAU object to be registered
|
176 |
+
* \param flags - Map flags
|
177 |
+
*
|
178 |
+
* \return
|
179 |
+
* ::cudaSuccess,
|
180 |
+
* ::cudaErrorInvalidDevice,
|
181 |
+
* ::cudaErrorInvalidValue,
|
182 |
+
* ::cudaErrorInvalidResourceHandle,
|
183 |
+
* ::cudaErrorUnknown
|
184 |
+
* \notefnerr
|
185 |
+
*
|
186 |
+
* \sa
|
187 |
+
* ::cudaVDPAUSetVDPAUDevice,
|
188 |
+
* ::cudaGraphicsUnregisterResource,
|
189 |
+
* ::cudaGraphicsSubResourceGetMappedArray,
|
190 |
+
* ::cuGraphicsVDPAURegisterOutputSurface
|
191 |
+
*/
|
192 |
+
extern __host__ cudaError_t CUDARTAPI cudaGraphicsVDPAURegisterOutputSurface(struct cudaGraphicsResource **resource, VdpOutputSurface vdpSurface, unsigned int flags);
|
193 |
+
|
194 |
+
/** @} */ /* END CUDART_VDPAU */
|
195 |
+
|
196 |
+
#if defined(__cplusplus)
|
197 |
+
}
|
198 |
+
#endif /* __cplusplus */
|
199 |
+
|
200 |
+
#endif /* __CUDA_VDPAU_INTEROP_H__ */
|
201 |
+
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_double_functions.h
ADDED
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2018 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
|
51 |
+
#if defined(_MSC_VER)
|
52 |
+
#pragma message("device_double_functions.h is an internal header file and must not be used directly. This file will be removed in a future CUDA release. Please use cuda_runtime_api.h or cuda_runtime.h instead.")
|
53 |
+
#else
|
54 |
+
#warning "device_double_functions.h is an internal header file and must not be used directly. This file will be removed in a future CUDA release. Please use cuda_runtime_api.h or cuda_runtime.h instead."
|
55 |
+
#endif
|
56 |
+
#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
57 |
+
#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_DOUBLE_FUNCTIONS_H_WRAPPER__
|
58 |
+
#endif
|
59 |
+
|
60 |
+
#include "crt/device_double_functions.h"
|
61 |
+
|
62 |
+
#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_DOUBLE_FUNCTIONS_H_WRAPPER__)
|
63 |
+
#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
64 |
+
#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_DOUBLE_FUNCTIONS_H_WRAPPER__
|
65 |
+
#endif
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/device_types.h
ADDED
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2018 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__DEVICE_TYPES_H__)
|
51 |
+
#define __DEVICE_TYPES_H__
|
52 |
+
|
53 |
+
#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
|
54 |
+
#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
55 |
+
#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_TYPES_H__
|
56 |
+
#endif
|
57 |
+
|
58 |
+
#ifndef __DOXYGEN_ONLY__
|
59 |
+
#include "crt/host_defines.h"
|
60 |
+
#endif
|
61 |
+
|
62 |
+
/*******************************************************************************
|
63 |
+
* *
|
64 |
+
* *
|
65 |
+
* *
|
66 |
+
*******************************************************************************/
|
67 |
+
|
68 |
+
enum __device_builtin__ cudaRoundMode
|
69 |
+
{
|
70 |
+
cudaRoundNearest,
|
71 |
+
cudaRoundZero,
|
72 |
+
cudaRoundPosInf,
|
73 |
+
cudaRoundMinInf
|
74 |
+
};
|
75 |
+
|
76 |
+
#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_TYPES_H__)
|
77 |
+
#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
78 |
+
#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_DEVICE_TYPES_H__
|
79 |
+
#endif
|
80 |
+
|
81 |
+
#endif /* !__DEVICE_TYPES_H__ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/driver_types.h
ADDED
The diff for this file is too large to render.
See raw diff
|
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/host_config.h
ADDED
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2018 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__)
|
51 |
+
#if defined(_MSC_VER)
|
52 |
+
#pragma message("host_config.h is an internal header file and must not be used directly. This file will be removed in a future CUDA release. Please use cuda_runtime_api.h or cuda_runtime.h instead.")
|
53 |
+
#else
|
54 |
+
#warning "host_config.h is an internal header file and must not be used directly. This file will be removed in a future CUDA release. Please use cuda_runtime_api.h or cuda_runtime.h instead."
|
55 |
+
#endif
|
56 |
+
#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
57 |
+
#define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_HOST_CONFIG_H_WRAPPER__
|
58 |
+
#endif
|
59 |
+
|
60 |
+
#include "crt/host_config.h"
|
61 |
+
|
62 |
+
#if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_HOST_CONFIG_H_WRAPPER__)
|
63 |
+
#undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
|
64 |
+
#undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_HOST_CONFIG_H_WRAPPER__
|
65 |
+
#endif
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/library_types.h
ADDED
@@ -0,0 +1,103 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2015 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__LIBRARY_TYPES_H__)
|
51 |
+
#define __LIBRARY_TYPES_H__
|
52 |
+
|
53 |
+
|
54 |
+
|
55 |
+
typedef enum cudaDataType_t
|
56 |
+
{
|
57 |
+
CUDA_R_16F = 2, /* real as a half */
|
58 |
+
CUDA_C_16F = 6, /* complex as a pair of half numbers */
|
59 |
+
CUDA_R_16BF = 14, /* real as a nv_bfloat16 */
|
60 |
+
CUDA_C_16BF = 15, /* complex as a pair of nv_bfloat16 numbers */
|
61 |
+
CUDA_R_32F = 0, /* real as a float */
|
62 |
+
CUDA_C_32F = 4, /* complex as a pair of float numbers */
|
63 |
+
CUDA_R_64F = 1, /* real as a double */
|
64 |
+
CUDA_C_64F = 5, /* complex as a pair of double numbers */
|
65 |
+
CUDA_R_4I = 16, /* real as a signed 4-bit int */
|
66 |
+
CUDA_C_4I = 17, /* complex as a pair of signed 4-bit int numbers */
|
67 |
+
CUDA_R_4U = 18, /* real as a unsigned 4-bit int */
|
68 |
+
CUDA_C_4U = 19, /* complex as a pair of unsigned 4-bit int numbers */
|
69 |
+
CUDA_R_8I = 3, /* real as a signed 8-bit int */
|
70 |
+
CUDA_C_8I = 7, /* complex as a pair of signed 8-bit int numbers */
|
71 |
+
CUDA_R_8U = 8, /* real as a unsigned 8-bit int */
|
72 |
+
CUDA_C_8U = 9, /* complex as a pair of unsigned 8-bit int numbers */
|
73 |
+
CUDA_R_16I = 20, /* real as a signed 16-bit int */
|
74 |
+
CUDA_C_16I = 21, /* complex as a pair of signed 16-bit int numbers */
|
75 |
+
CUDA_R_16U = 22, /* real as a unsigned 16-bit int */
|
76 |
+
CUDA_C_16U = 23, /* complex as a pair of unsigned 16-bit int numbers */
|
77 |
+
CUDA_R_32I = 10, /* real as a signed 32-bit int */
|
78 |
+
CUDA_C_32I = 11, /* complex as a pair of signed 32-bit int numbers */
|
79 |
+
CUDA_R_32U = 12, /* real as a unsigned 32-bit int */
|
80 |
+
CUDA_C_32U = 13, /* complex as a pair of unsigned 32-bit int numbers */
|
81 |
+
CUDA_R_64I = 24, /* real as a signed 64-bit int */
|
82 |
+
CUDA_C_64I = 25, /* complex as a pair of signed 64-bit int numbers */
|
83 |
+
CUDA_R_64U = 26, /* real as a unsigned 64-bit int */
|
84 |
+
CUDA_C_64U = 27, /* complex as a pair of unsigned 64-bit int numbers */
|
85 |
+
CUDA_R_8F_E4M3 = 28, /* real as a nv_fp8_e4m3 */
|
86 |
+
CUDA_R_8F_E5M2 = 29, /* real as a nv_fp8_e5m2 */
|
87 |
+
} cudaDataType;
|
88 |
+
|
89 |
+
|
90 |
+
typedef enum libraryPropertyType_t
|
91 |
+
{
|
92 |
+
MAJOR_VERSION,
|
93 |
+
MINOR_VERSION,
|
94 |
+
PATCH_LEVEL
|
95 |
+
} libraryPropertyType;
|
96 |
+
|
97 |
+
|
98 |
+
#ifndef __cplusplus
|
99 |
+
typedef enum cudaDataType_t cudaDataType_t;
|
100 |
+
typedef enum libraryPropertyType_t libraryPropertyType_t;
|
101 |
+
#endif
|
102 |
+
|
103 |
+
#endif /* !__LIBRARY_TYPES_H__ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/math_constants.h
ADDED
@@ -0,0 +1,152 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2021 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__MATH_CONSTANTS_H__)
|
51 |
+
#define __MATH_CONSTANTS_H__
|
52 |
+
|
53 |
+
/* single precision constants */
|
54 |
+
#define CUDART_INF_F __int_as_float(0x7f800000U)
|
55 |
+
#define CUDART_NAN_F __int_as_float(0x7fffffffU)
|
56 |
+
#define CUDART_MIN_DENORM_F __int_as_float(0x00000001U)
|
57 |
+
#define CUDART_MAX_NORMAL_F __int_as_float(0x7f7fffffU)
|
58 |
+
#define CUDART_NEG_ZERO_F __int_as_float(0x80000000U)
|
59 |
+
#define CUDART_ZERO_F 0.0F
|
60 |
+
#define CUDART_ONE_F 1.0F
|
61 |
+
#define CUDART_SQRT_HALF_F 0.707106781F
|
62 |
+
#define CUDART_SQRT_HALF_HI_F 0.707106781F
|
63 |
+
#define CUDART_SQRT_HALF_LO_F 1.210161749e-08F
|
64 |
+
#define CUDART_SQRT_TWO_F 1.414213562F
|
65 |
+
#define CUDART_THIRD_F 0.333333333F
|
66 |
+
#define CUDART_PIO4_F 0.785398163F
|
67 |
+
#define CUDART_PIO2_F 1.570796327F
|
68 |
+
#define CUDART_3PIO4_F 2.356194490F
|
69 |
+
#define CUDART_2_OVER_PI_F 0.636619772F
|
70 |
+
#define CUDART_SQRT_2_OVER_PI_F 0.797884561F
|
71 |
+
#define CUDART_PI_F 3.141592654F
|
72 |
+
#define CUDART_L2E_F 1.442695041F
|
73 |
+
#define CUDART_L2T_F 3.321928094F
|
74 |
+
#define CUDART_LG2_F 0.301029996F
|
75 |
+
#define CUDART_LGE_F 0.434294482F
|
76 |
+
#define CUDART_LN2_F 0.693147181F
|
77 |
+
#define CUDART_LNT_F 2.302585093F
|
78 |
+
#define CUDART_LNPI_F 1.144729886F
|
79 |
+
#define CUDART_TWO_TO_M126_F 1.175494351e-38F
|
80 |
+
#define CUDART_TWO_TO_126_F 8.507059173e37F
|
81 |
+
#define CUDART_NORM_HUGE_F 3.402823466e38F
|
82 |
+
#define CUDART_TWO_TO_23_F 8388608.0F
|
83 |
+
#define CUDART_TWO_TO_24_F 16777216.0F
|
84 |
+
#define CUDART_TWO_TO_31_F 2147483648.0F
|
85 |
+
#define CUDART_TWO_TO_32_F 4294967296.0F
|
86 |
+
#define CUDART_REMQUO_BITS_F 3U
|
87 |
+
#define CUDART_REMQUO_MASK_F (~((~0U)<<CUDART_REMQUO_BITS_F))
|
88 |
+
#define CUDART_TRIG_PLOSS_F 105615.0F
|
89 |
+
|
90 |
+
/* double precision constants */
|
91 |
+
#define CUDART_INF __longlong_as_double(0x7ff0000000000000ULL)
|
92 |
+
#define CUDART_NAN __longlong_as_double(0xfff8000000000000ULL)
|
93 |
+
#define CUDART_NEG_ZERO __longlong_as_double(0x8000000000000000ULL)
|
94 |
+
#define CUDART_MIN_DENORM __longlong_as_double(0x0000000000000001ULL)
|
95 |
+
#define CUDART_ZERO 0.0
|
96 |
+
#define CUDART_ONE 1.0
|
97 |
+
#define CUDART_SQRT_TWO 1.4142135623730951e+0
|
98 |
+
#define CUDART_SQRT_HALF 7.0710678118654757e-1
|
99 |
+
#define CUDART_SQRT_HALF_HI 7.0710678118654757e-1
|
100 |
+
#define CUDART_SQRT_HALF_LO (-4.8336466567264567e-17)
|
101 |
+
#define CUDART_THIRD 3.3333333333333333e-1
|
102 |
+
#define CUDART_TWOTHIRD 6.6666666666666667e-1
|
103 |
+
#define CUDART_PIO4 7.8539816339744828e-1
|
104 |
+
#define CUDART_PIO4_HI 7.8539816339744828e-1
|
105 |
+
#define CUDART_PIO4_LO 3.0616169978683830e-17
|
106 |
+
#define CUDART_PIO2 1.5707963267948966e+0
|
107 |
+
#define CUDART_PIO2_HI 1.5707963267948966e+0
|
108 |
+
#define CUDART_PIO2_LO 6.1232339957367660e-17
|
109 |
+
#define CUDART_3PIO4 2.3561944901923448e+0
|
110 |
+
#define CUDART_2_OVER_PI 6.3661977236758138e-1
|
111 |
+
#define CUDART_PI 3.1415926535897931e+0
|
112 |
+
#define CUDART_PI_HI 3.1415926535897931e+0
|
113 |
+
#define CUDART_PI_LO 1.2246467991473532e-16
|
114 |
+
#define CUDART_SQRT_2PI 2.5066282746310007e+0
|
115 |
+
#define CUDART_SQRT_2PI_HI 2.5066282746310007e+0
|
116 |
+
#define CUDART_SQRT_2PI_LO (-1.8328579980459167e-16)
|
117 |
+
#define CUDART_SQRT_PIO2 1.2533141373155003e+0
|
118 |
+
#define CUDART_SQRT_PIO2_HI 1.2533141373155003e+0
|
119 |
+
#define CUDART_SQRT_PIO2_LO (-9.1642899902295834e-17)
|
120 |
+
#define CUDART_SQRT_2OPI 7.9788456080286536e-1
|
121 |
+
#define CUDART_L2E 1.4426950408889634e+0
|
122 |
+
#define CUDART_L2E_HI 1.4426950408889634e+0
|
123 |
+
#define CUDART_L2E_LO 2.0355273740931033e-17
|
124 |
+
#define CUDART_L2T 3.3219280948873622e+0
|
125 |
+
#define CUDART_LG2 3.0102999566398120e-1
|
126 |
+
#define CUDART_LG2_HI 3.0102999566398120e-1
|
127 |
+
#define CUDART_LG2_LO (-2.8037281277851704e-18)
|
128 |
+
#define CUDART_LGE 4.3429448190325182e-1
|
129 |
+
#define CUDART_LGE_HI 4.3429448190325182e-1
|
130 |
+
#define CUDART_LGE_LO 1.09831965021676510e-17
|
131 |
+
#define CUDART_LN2 6.9314718055994529e-1
|
132 |
+
#define CUDART_LN2_HI 6.9314718055994529e-1
|
133 |
+
#define CUDART_LN2_LO 2.3190468138462996e-17
|
134 |
+
#define CUDART_LNT 2.3025850929940459e+0
|
135 |
+
#define CUDART_LNT_HI 2.3025850929940459e+0
|
136 |
+
#define CUDART_LNT_LO (-2.1707562233822494e-16)
|
137 |
+
#define CUDART_LNPI 1.1447298858494002e+0
|
138 |
+
#define CUDART_LN2_X_1024 7.0978271289338397e+2
|
139 |
+
#define CUDART_LN2_X_1025 7.1047586007394398e+2
|
140 |
+
#define CUDART_LN2_X_1075 7.4513321910194122e+2
|
141 |
+
#define CUDART_LG2_X_1024 3.0825471555991675e+2
|
142 |
+
#define CUDART_LG2_X_1075 3.2360724533877976e+2
|
143 |
+
#define CUDART_TWO_TO_23 8388608.0
|
144 |
+
#define CUDART_TWO_TO_52 4503599627370496.0
|
145 |
+
#define CUDART_TWO_TO_53 9007199254740992.0
|
146 |
+
#define CUDART_TWO_TO_54 18014398509481984.0
|
147 |
+
#define CUDART_TWO_TO_M54 5.5511151231257827e-17
|
148 |
+
#define CUDART_TWO_TO_M1022 2.22507385850720140e-308
|
149 |
+
#define CUDART_TRIG_PLOSS 2147483648.0
|
150 |
+
#define CUDART_DBL2INT_CVT 6755399441055744.0
|
151 |
+
|
152 |
+
#endif /* !__MATH_CONSTANTS_H__ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_atomic_functions.h
ADDED
@@ -0,0 +1,141 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2014 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 35.235 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.35.235 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__SM_32_ATOMIC_FUNCTIONS_H__)
|
51 |
+
#define __SM_32_ATOMIC_FUNCTIONS_H__
|
52 |
+
|
53 |
+
#if defined(__CUDACC_RTC__)
|
54 |
+
#define __SM_32_ATOMIC_FUNCTIONS_DECL__ __device__
|
55 |
+
#else /* !__CUDACC_RTC__ */
|
56 |
+
#define __SM_32_ATOMIC_FUNCTIONS_DECL__ static __inline__ __device__
|
57 |
+
#endif /* __CUDACC_RTC__ */
|
58 |
+
|
59 |
+
#if defined(__cplusplus) && defined(__CUDACC__)
|
60 |
+
|
61 |
+
#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 320
|
62 |
+
|
63 |
+
/*******************************************************************************
|
64 |
+
* *
|
65 |
+
* *
|
66 |
+
* *
|
67 |
+
*******************************************************************************/
|
68 |
+
|
69 |
+
#include "cuda_runtime_api.h"
|
70 |
+
|
71 |
+
#if defined(_NVHPC_CUDA)
|
72 |
+
#undef __device_builtin__
|
73 |
+
#define __device_builtin__ __location__(device) __location__(host)
|
74 |
+
#endif /* _NVHPC_CUDA */
|
75 |
+
|
76 |
+
#ifndef __CUDA_ARCH__
|
77 |
+
#define __DEF_IF_HOST { }
|
78 |
+
#else /* !__CUDA_ARCH__ */
|
79 |
+
#define __DEF_IF_HOST ;
|
80 |
+
#endif /* __CUDA_ARCH__ */
|
81 |
+
|
82 |
+
|
83 |
+
#ifdef __CUDA_ARCH__
|
84 |
+
extern "C"
|
85 |
+
{
|
86 |
+
extern __device__ __device_builtin__ long long __illAtomicMin(long long *address, long long val);
|
87 |
+
extern __device__ __device_builtin__ long long __illAtomicMax(long long *address, long long val);
|
88 |
+
extern __device__ __device_builtin__ long long __llAtomicAnd(long long *address, long long val);
|
89 |
+
extern __device__ __device_builtin__ long long __llAtomicOr(long long *address, long long val);
|
90 |
+
extern __device__ __device_builtin__ long long __llAtomicXor(long long *address, long long val);
|
91 |
+
extern __device__ __device_builtin__ unsigned long long __ullAtomicMin(unsigned long long *address, unsigned long long val);
|
92 |
+
extern __device__ __device_builtin__ unsigned long long __ullAtomicMax(unsigned long long *address, unsigned long long val);
|
93 |
+
extern __device__ __device_builtin__ unsigned long long __ullAtomicAnd(unsigned long long *address, unsigned long long val);
|
94 |
+
extern __device__ __device_builtin__ unsigned long long __ullAtomicOr (unsigned long long *address, unsigned long long val);
|
95 |
+
extern __device__ __device_builtin__ unsigned long long __ullAtomicXor(unsigned long long *address, unsigned long long val);
|
96 |
+
}
|
97 |
+
#endif /* __CUDA_ARCH__ */
|
98 |
+
|
99 |
+
#if defined(_NVHPC_CUDA)
|
100 |
+
#undef __device_builtin__
|
101 |
+
#define __device_builtin__
|
102 |
+
#endif /* _NVHPC_CUDA */
|
103 |
+
|
104 |
+
/*******************************************************************************
|
105 |
+
* *
|
106 |
+
* *
|
107 |
+
* *
|
108 |
+
*******************************************************************************/
|
109 |
+
|
110 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicMin(long long *address, long long val) __DEF_IF_HOST
|
111 |
+
|
112 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicMax(long long *address, long long val) __DEF_IF_HOST
|
113 |
+
|
114 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicAnd(long long *address, long long val) __DEF_IF_HOST
|
115 |
+
|
116 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicOr(long long *address, long long val) __DEF_IF_HOST
|
117 |
+
|
118 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ long long atomicXor(long long *address, long long val) __DEF_IF_HOST
|
119 |
+
|
120 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicMin(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
|
121 |
+
|
122 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicMax(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
|
123 |
+
|
124 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicAnd(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
|
125 |
+
|
126 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicOr(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
|
127 |
+
|
128 |
+
__SM_32_ATOMIC_FUNCTIONS_DECL__ unsigned long long atomicXor(unsigned long long *address, unsigned long long val) __DEF_IF_HOST
|
129 |
+
|
130 |
+
#endif /* !__CUDA_ARCH__ || __CUDA_ARCH__ >= 320 */
|
131 |
+
|
132 |
+
#endif /* __cplusplus && __CUDACC__ */
|
133 |
+
|
134 |
+
#undef __DEF_IF_HOST
|
135 |
+
#undef __SM_32_ATOMIC_FUNCTIONS_DECL__
|
136 |
+
|
137 |
+
#if !defined(__CUDACC_RTC__) && defined(__CUDA_ARCH__)
|
138 |
+
#include "sm_32_atomic_functions.hpp"
|
139 |
+
#endif /* !__CUDACC_RTC__ && defined(__CUDA_ARCH__) */
|
140 |
+
|
141 |
+
#endif /* !__SM_32_ATOMIC_FUNCTIONS_H__ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/sm_32_intrinsics.hpp
ADDED
@@ -0,0 +1,588 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
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|
|
|
|
|
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|
|
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|
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1 |
+
/*
|
2 |
+
* Copyright 1993-2020 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__SM_32_INTRINSICS_HPP__)
|
51 |
+
#define __SM_32_INTRINSICS_HPP__
|
52 |
+
|
53 |
+
#if defined(__CUDACC_RTC__)
|
54 |
+
#define __SM_32_INTRINSICS_DECL__ __device__
|
55 |
+
#else /* !__CUDACC_RTC__ */
|
56 |
+
#define __SM_32_INTRINSICS_DECL__ static __device__ __inline__
|
57 |
+
#endif /* __CUDACC_RTC__ */
|
58 |
+
|
59 |
+
#if defined(__cplusplus) && defined(__CUDACC__)
|
60 |
+
|
61 |
+
#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 320
|
62 |
+
|
63 |
+
/*******************************************************************************
|
64 |
+
* *
|
65 |
+
* *
|
66 |
+
* *
|
67 |
+
*******************************************************************************/
|
68 |
+
|
69 |
+
#include "cuda_runtime_api.h"
|
70 |
+
|
71 |
+
// In here are intrinsics which are built in to the compiler. These may be
|
72 |
+
// referenced by intrinsic implementations from this file.
|
73 |
+
extern "C"
|
74 |
+
{
|
75 |
+
// There are no intrinsics built in to the compiler for SM-3.5,
|
76 |
+
// all intrinsics are now implemented as inline PTX below.
|
77 |
+
}
|
78 |
+
|
79 |
+
/*******************************************************************************
|
80 |
+
* *
|
81 |
+
* Below are implementations of SM-3.5 intrinsics which are included as *
|
82 |
+
* source (instead of being built in to the compiler) *
|
83 |
+
* *
|
84 |
+
*******************************************************************************/
|
85 |
+
|
86 |
+
// LDG is a "load from global via texture path" command which can exhibit higher
|
87 |
+
// bandwidth on GK110 than a regular LD.
|
88 |
+
// Define a different pointer storage size for 64 and 32 bit
|
89 |
+
#if (defined(_MSC_VER) && defined(_WIN64)) || defined(__LP64__) || defined(__CUDACC_RTC__)
|
90 |
+
#define __LDG_PTR "l"
|
91 |
+
#else
|
92 |
+
#define __LDG_PTR "r"
|
93 |
+
#endif
|
94 |
+
|
95 |
+
/******************************************************************************
|
96 |
+
* __ldg *
|
97 |
+
******************************************************************************/
|
98 |
+
|
99 |
+
// Size of long is architecture and OS specific.
|
100 |
+
#if defined(__LP64__) // 64 bits
|
101 |
+
__SM_32_INTRINSICS_DECL__ long __ldg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
102 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
103 |
+
#else // 32 bits
|
104 |
+
__SM_32_INTRINSICS_DECL__ long __ldg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
105 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.nc.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
106 |
+
#endif
|
107 |
+
|
108 |
+
|
109 |
+
__SM_32_INTRINSICS_DECL__ char __ldg(const char *ptr) { unsigned int ret; asm volatile ("ld.global.nc.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
|
110 |
+
__SM_32_INTRINSICS_DECL__ signed char __ldg(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.nc.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
|
111 |
+
__SM_32_INTRINSICS_DECL__ short __ldg(const short *ptr) { unsigned short ret; asm volatile ("ld.global.nc.s16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
|
112 |
+
__SM_32_INTRINSICS_DECL__ int __ldg(const int *ptr) { unsigned int ret; asm volatile ("ld.global.nc.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
|
113 |
+
__SM_32_INTRINSICS_DECL__ long long __ldg(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.nc.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
|
114 |
+
__SM_32_INTRINSICS_DECL__ char2 __ldg(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.nc.v2.s8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
|
115 |
+
__SM_32_INTRINSICS_DECL__ char4 __ldg(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.nc.v4.s8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
|
116 |
+
__SM_32_INTRINSICS_DECL__ short2 __ldg(const short2 *ptr) { short2 ret; asm volatile ("ld.global.nc.v2.s16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
117 |
+
__SM_32_INTRINSICS_DECL__ short4 __ldg(const short4 *ptr) { short4 ret; asm volatile ("ld.global.nc.v4.s16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
118 |
+
__SM_32_INTRINSICS_DECL__ int2 __ldg(const int2 *ptr) { int2 ret; asm volatile ("ld.global.nc.v2.s32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
119 |
+
__SM_32_INTRINSICS_DECL__ int4 __ldg(const int4 *ptr) { int4 ret; asm volatile ("ld.global.nc.v4.s32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
120 |
+
__SM_32_INTRINSICS_DECL__ longlong2 __ldg(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.nc.v2.s64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
121 |
+
|
122 |
+
__SM_32_INTRINSICS_DECL__ unsigned char __ldg(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.nc.u8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (unsigned char)ret; }
|
123 |
+
__SM_32_INTRINSICS_DECL__ unsigned short __ldg(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.nc.u16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
|
124 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __ldg(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.nc.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
125 |
+
__SM_32_INTRINSICS_DECL__ unsigned long long __ldg(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.nc.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
126 |
+
__SM_32_INTRINSICS_DECL__ uchar2 __ldg(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.nc.v2.u8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
|
127 |
+
__SM_32_INTRINSICS_DECL__ uchar4 __ldg(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.nc.v4.u8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
|
128 |
+
__SM_32_INTRINSICS_DECL__ ushort2 __ldg(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.nc.v2.u16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
129 |
+
__SM_32_INTRINSICS_DECL__ ushort4 __ldg(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.nc.v4.u16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
130 |
+
__SM_32_INTRINSICS_DECL__ uint2 __ldg(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.nc.v2.u32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
131 |
+
__SM_32_INTRINSICS_DECL__ uint4 __ldg(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.nc.v4.u32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
132 |
+
__SM_32_INTRINSICS_DECL__ ulonglong2 __ldg(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.nc.v2.u64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
133 |
+
|
134 |
+
__SM_32_INTRINSICS_DECL__ float __ldg(const float *ptr) { float ret; asm volatile ("ld.global.nc.f32 %0, [%1];" : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
|
135 |
+
__SM_32_INTRINSICS_DECL__ double __ldg(const double *ptr) { double ret; asm volatile ("ld.global.nc.f64 %0, [%1];" : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
|
136 |
+
__SM_32_INTRINSICS_DECL__ float2 __ldg(const float2 *ptr) { float2 ret; asm volatile ("ld.global.nc.v2.f32 {%0,%1}, [%2];" : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
137 |
+
__SM_32_INTRINSICS_DECL__ float4 __ldg(const float4 *ptr) { float4 ret; asm volatile ("ld.global.nc.v4.f32 {%0,%1,%2,%3}, [%4];" : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
138 |
+
__SM_32_INTRINSICS_DECL__ double2 __ldg(const double2 *ptr) { double2 ret; asm volatile ("ld.global.nc.v2.f64 {%0,%1}, [%2];" : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
139 |
+
|
140 |
+
|
141 |
+
/******************************************************************************
|
142 |
+
* __ldcg *
|
143 |
+
******************************************************************************/
|
144 |
+
|
145 |
+
// Size of long is architecture and OS specific.
|
146 |
+
#if defined(__LP64__) // 64 bits
|
147 |
+
__SM_32_INTRINSICS_DECL__ long __ldcg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
148 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldcg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
149 |
+
#else // 32 bits
|
150 |
+
__SM_32_INTRINSICS_DECL__ long __ldcg(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
151 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldcg(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cg.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
152 |
+
#endif
|
153 |
+
|
154 |
+
|
155 |
+
__SM_32_INTRINSICS_DECL__ char __ldcg(const char *ptr) { unsigned int ret; asm volatile ("ld.global.cg.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
|
156 |
+
__SM_32_INTRINSICS_DECL__ signed char __ldcg(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.cg.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
|
157 |
+
__SM_32_INTRINSICS_DECL__ short __ldcg(const short *ptr) { unsigned short ret; asm volatile ("ld.global.cg.s16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
|
158 |
+
__SM_32_INTRINSICS_DECL__ int __ldcg(const int *ptr) { unsigned int ret; asm volatile ("ld.global.cg.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
|
159 |
+
__SM_32_INTRINSICS_DECL__ long long __ldcg(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cg.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
|
160 |
+
__SM_32_INTRINSICS_DECL__ char2 __ldcg(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.cg.v2.s8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
|
161 |
+
__SM_32_INTRINSICS_DECL__ char4 __ldcg(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.cg.v4.s8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
|
162 |
+
__SM_32_INTRINSICS_DECL__ short2 __ldcg(const short2 *ptr) { short2 ret; asm volatile ("ld.global.cg.v2.s16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
163 |
+
__SM_32_INTRINSICS_DECL__ short4 __ldcg(const short4 *ptr) { short4 ret; asm volatile ("ld.global.cg.v4.s16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
164 |
+
__SM_32_INTRINSICS_DECL__ int2 __ldcg(const int2 *ptr) { int2 ret; asm volatile ("ld.global.cg.v2.s32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
165 |
+
__SM_32_INTRINSICS_DECL__ int4 __ldcg(const int4 *ptr) { int4 ret; asm volatile ("ld.global.cg.v4.s32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
166 |
+
__SM_32_INTRINSICS_DECL__ longlong2 __ldcg(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.cg.v2.s64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
167 |
+
|
168 |
+
__SM_32_INTRINSICS_DECL__ unsigned char __ldcg(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.cg.u8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (unsigned char)ret; }
|
169 |
+
__SM_32_INTRINSICS_DECL__ unsigned short __ldcg(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.cg.u16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
|
170 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __ldcg(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.cg.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
171 |
+
__SM_32_INTRINSICS_DECL__ unsigned long long __ldcg(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cg.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
172 |
+
__SM_32_INTRINSICS_DECL__ uchar2 __ldcg(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.cg.v2.u8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
|
173 |
+
__SM_32_INTRINSICS_DECL__ uchar4 __ldcg(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.cg.v4.u8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
|
174 |
+
__SM_32_INTRINSICS_DECL__ ushort2 __ldcg(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.cg.v2.u16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
175 |
+
__SM_32_INTRINSICS_DECL__ ushort4 __ldcg(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.cg.v4.u16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
176 |
+
__SM_32_INTRINSICS_DECL__ uint2 __ldcg(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.cg.v2.u32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
177 |
+
__SM_32_INTRINSICS_DECL__ uint4 __ldcg(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.cg.v4.u32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
178 |
+
__SM_32_INTRINSICS_DECL__ ulonglong2 __ldcg(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.cg.v2.u64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
179 |
+
|
180 |
+
__SM_32_INTRINSICS_DECL__ float __ldcg(const float *ptr) { float ret; asm volatile ("ld.global.cg.f32 %0, [%1];" : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
|
181 |
+
__SM_32_INTRINSICS_DECL__ double __ldcg(const double *ptr) { double ret; asm volatile ("ld.global.cg.f64 %0, [%1];" : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
|
182 |
+
__SM_32_INTRINSICS_DECL__ float2 __ldcg(const float2 *ptr) { float2 ret; asm volatile ("ld.global.cg.v2.f32 {%0,%1}, [%2];" : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
183 |
+
__SM_32_INTRINSICS_DECL__ float4 __ldcg(const float4 *ptr) { float4 ret; asm volatile ("ld.global.cg.v4.f32 {%0,%1,%2,%3}, [%4];" : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
184 |
+
__SM_32_INTRINSICS_DECL__ double2 __ldcg(const double2 *ptr) { double2 ret; asm volatile ("ld.global.cg.v2.f64 {%0,%1}, [%2];" : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
185 |
+
|
186 |
+
/******************************************************************************
|
187 |
+
* __ldca *
|
188 |
+
******************************************************************************/
|
189 |
+
|
190 |
+
// Size of long is architecture and OS specific.
|
191 |
+
#if defined(__LP64__) // 64 bits
|
192 |
+
__SM_32_INTRINSICS_DECL__ long __ldca(const long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
193 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldca(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
194 |
+
#else // 32 bits
|
195 |
+
__SM_32_INTRINSICS_DECL__ long __ldca(const long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
196 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldca(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.ca.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
197 |
+
#endif
|
198 |
+
|
199 |
+
|
200 |
+
__SM_32_INTRINSICS_DECL__ char __ldca(const char *ptr) { unsigned int ret; asm volatile ("ld.global.ca.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
|
201 |
+
__SM_32_INTRINSICS_DECL__ signed char __ldca(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.ca.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
|
202 |
+
__SM_32_INTRINSICS_DECL__ short __ldca(const short *ptr) { unsigned short ret; asm volatile ("ld.global.ca.s16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
|
203 |
+
__SM_32_INTRINSICS_DECL__ int __ldca(const int *ptr) { unsigned int ret; asm volatile ("ld.global.ca.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
|
204 |
+
__SM_32_INTRINSICS_DECL__ long long __ldca(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.ca.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
|
205 |
+
__SM_32_INTRINSICS_DECL__ char2 __ldca(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.ca.v2.s8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
|
206 |
+
__SM_32_INTRINSICS_DECL__ char4 __ldca(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.ca.v4.s8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
|
207 |
+
__SM_32_INTRINSICS_DECL__ short2 __ldca(const short2 *ptr) { short2 ret; asm volatile ("ld.global.ca.v2.s16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
208 |
+
__SM_32_INTRINSICS_DECL__ short4 __ldca(const short4 *ptr) { short4 ret; asm volatile ("ld.global.ca.v4.s16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
209 |
+
__SM_32_INTRINSICS_DECL__ int2 __ldca(const int2 *ptr) { int2 ret; asm volatile ("ld.global.ca.v2.s32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
210 |
+
__SM_32_INTRINSICS_DECL__ int4 __ldca(const int4 *ptr) { int4 ret; asm volatile ("ld.global.ca.v4.s32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
211 |
+
__SM_32_INTRINSICS_DECL__ longlong2 __ldca(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.ca.v2.s64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
212 |
+
|
213 |
+
__SM_32_INTRINSICS_DECL__ unsigned char __ldca(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.ca.u8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (unsigned char)ret; }
|
214 |
+
__SM_32_INTRINSICS_DECL__ unsigned short __ldca(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.ca.u16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
|
215 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __ldca(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.ca.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
216 |
+
__SM_32_INTRINSICS_DECL__ unsigned long long __ldca(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.ca.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
217 |
+
__SM_32_INTRINSICS_DECL__ uchar2 __ldca(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.ca.v2.u8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
|
218 |
+
__SM_32_INTRINSICS_DECL__ uchar4 __ldca(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.ca.v4.u8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
|
219 |
+
__SM_32_INTRINSICS_DECL__ ushort2 __ldca(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.ca.v2.u16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
220 |
+
__SM_32_INTRINSICS_DECL__ ushort4 __ldca(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.ca.v4.u16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
221 |
+
__SM_32_INTRINSICS_DECL__ uint2 __ldca(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.ca.v2.u32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
222 |
+
__SM_32_INTRINSICS_DECL__ uint4 __ldca(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.ca.v4.u32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
223 |
+
__SM_32_INTRINSICS_DECL__ ulonglong2 __ldca(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.ca.v2.u64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
224 |
+
|
225 |
+
__SM_32_INTRINSICS_DECL__ float __ldca(const float *ptr) { float ret; asm volatile ("ld.global.ca.f32 %0, [%1];" : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
|
226 |
+
__SM_32_INTRINSICS_DECL__ double __ldca(const double *ptr) { double ret; asm volatile ("ld.global.ca.f64 %0, [%1];" : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
|
227 |
+
__SM_32_INTRINSICS_DECL__ float2 __ldca(const float2 *ptr) { float2 ret; asm volatile ("ld.global.ca.v2.f32 {%0,%1}, [%2];" : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
228 |
+
__SM_32_INTRINSICS_DECL__ float4 __ldca(const float4 *ptr) { float4 ret; asm volatile ("ld.global.ca.v4.f32 {%0,%1,%2,%3}, [%4];" : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
229 |
+
__SM_32_INTRINSICS_DECL__ double2 __ldca(const double2 *ptr) { double2 ret; asm volatile ("ld.global.ca.v2.f64 {%0,%1}, [%2];" : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
230 |
+
|
231 |
+
/******************************************************************************
|
232 |
+
* __ldcs *
|
233 |
+
******************************************************************************/
|
234 |
+
|
235 |
+
// Size of long is architecture and OS specific.
|
236 |
+
#if defined(__LP64__) // 64 bits
|
237 |
+
__SM_32_INTRINSICS_DECL__ long __ldcs(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
238 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldcs(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
239 |
+
#else // 32 bits
|
240 |
+
__SM_32_INTRINSICS_DECL__ long __ldcs(const long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (long)ret; }
|
241 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldcs(const unsigned long *ptr) { unsigned long ret; asm volatile ("ld.global.cs.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
242 |
+
#endif
|
243 |
+
|
244 |
+
|
245 |
+
__SM_32_INTRINSICS_DECL__ char __ldcs(const char *ptr) { unsigned int ret; asm volatile ("ld.global.cs.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (char)ret; }
|
246 |
+
__SM_32_INTRINSICS_DECL__ signed char __ldcs(const signed char *ptr) { unsigned int ret; asm volatile ("ld.global.cs.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (signed char)ret; }
|
247 |
+
__SM_32_INTRINSICS_DECL__ short __ldcs(const short *ptr) { unsigned short ret; asm volatile ("ld.global.cs.s16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return (short)ret; }
|
248 |
+
__SM_32_INTRINSICS_DECL__ int __ldcs(const int *ptr) { unsigned int ret; asm volatile ("ld.global.cs.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (int)ret; }
|
249 |
+
__SM_32_INTRINSICS_DECL__ long long __ldcs(const long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cs.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return (long long)ret; }
|
250 |
+
__SM_32_INTRINSICS_DECL__ char2 __ldcs(const char2 *ptr) { char2 ret; int2 tmp; asm volatile ("ld.global.cs.v2.s8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
|
251 |
+
__SM_32_INTRINSICS_DECL__ char4 __ldcs(const char4 *ptr) { char4 ret; int4 tmp; asm volatile ("ld.global.cs.v4.s8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
|
252 |
+
__SM_32_INTRINSICS_DECL__ short2 __ldcs(const short2 *ptr) { short2 ret; asm volatile ("ld.global.cs.v2.s16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
253 |
+
__SM_32_INTRINSICS_DECL__ short4 __ldcs(const short4 *ptr) { short4 ret; asm volatile ("ld.global.cs.v4.s16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
254 |
+
__SM_32_INTRINSICS_DECL__ int2 __ldcs(const int2 *ptr) { int2 ret; asm volatile ("ld.global.cs.v2.s32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
255 |
+
__SM_32_INTRINSICS_DECL__ int4 __ldcs(const int4 *ptr) { int4 ret; asm volatile ("ld.global.cs.v4.s32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
256 |
+
__SM_32_INTRINSICS_DECL__ longlong2 __ldcs(const longlong2 *ptr) { longlong2 ret; asm volatile ("ld.global.cs.v2.s64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
257 |
+
|
258 |
+
__SM_32_INTRINSICS_DECL__ unsigned char __ldcs(const unsigned char *ptr) { unsigned int ret; asm volatile ("ld.global.cs.u8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return (unsigned char)ret; }
|
259 |
+
__SM_32_INTRINSICS_DECL__ unsigned short __ldcs(const unsigned short *ptr) { unsigned short ret; asm volatile ("ld.global.cs.u16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr)); return ret; }
|
260 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __ldcs(const unsigned int *ptr) { unsigned int ret; asm volatile ("ld.global.cs.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr)); return ret; }
|
261 |
+
__SM_32_INTRINSICS_DECL__ unsigned long long __ldcs(const unsigned long long *ptr) { unsigned long long ret; asm volatile ("ld.global.cs.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr)); return ret; }
|
262 |
+
__SM_32_INTRINSICS_DECL__ uchar2 __ldcs(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm volatile ("ld.global.cs.v2.u8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
|
263 |
+
__SM_32_INTRINSICS_DECL__ uchar4 __ldcs(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm volatile ("ld.global.cs.v4.u8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr)); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
|
264 |
+
__SM_32_INTRINSICS_DECL__ ushort2 __ldcs(const ushort2 *ptr) { ushort2 ret; asm volatile ("ld.global.cs.v2.u16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
265 |
+
__SM_32_INTRINSICS_DECL__ ushort4 __ldcs(const ushort4 *ptr) { ushort4 ret; asm volatile ("ld.global.cs.v4.u16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
266 |
+
__SM_32_INTRINSICS_DECL__ uint2 __ldcs(const uint2 *ptr) { uint2 ret; asm volatile ("ld.global.cs.v2.u32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
267 |
+
__SM_32_INTRINSICS_DECL__ uint4 __ldcs(const uint4 *ptr) { uint4 ret; asm volatile ("ld.global.cs.v4.u32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
268 |
+
__SM_32_INTRINSICS_DECL__ ulonglong2 __ldcs(const ulonglong2 *ptr) { ulonglong2 ret; asm volatile ("ld.global.cs.v2.u64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
269 |
+
|
270 |
+
__SM_32_INTRINSICS_DECL__ float __ldcs(const float *ptr) { float ret; asm volatile ("ld.global.cs.f32 %0, [%1];" : "=f"(ret) : __LDG_PTR (ptr)); return ret; }
|
271 |
+
__SM_32_INTRINSICS_DECL__ double __ldcs(const double *ptr) { double ret; asm volatile ("ld.global.cs.f64 %0, [%1];" : "=d"(ret) : __LDG_PTR (ptr)); return ret; }
|
272 |
+
__SM_32_INTRINSICS_DECL__ float2 __ldcs(const float2 *ptr) { float2 ret; asm volatile ("ld.global.cs.v2.f32 {%0,%1}, [%2];" : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
273 |
+
__SM_32_INTRINSICS_DECL__ float4 __ldcs(const float4 *ptr) { float4 ret; asm volatile ("ld.global.cs.v4.f32 {%0,%1,%2,%3}, [%4];" : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr)); return ret; }
|
274 |
+
__SM_32_INTRINSICS_DECL__ double2 __ldcs(const double2 *ptr) { double2 ret; asm volatile ("ld.global.cs.v2.f64 {%0,%1}, [%2];" : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr)); return ret; }
|
275 |
+
|
276 |
+
/******************************************************************************
|
277 |
+
* __ldlu *
|
278 |
+
******************************************************************************/
|
279 |
+
|
280 |
+
// Size of long is architecture and OS specific.
|
281 |
+
#if defined(__LP64__) // 64 bits
|
282 |
+
__SM_32_INTRINSICS_DECL__ long __ldlu(const long *ptr) { unsigned long ret; asm ("ld.global.lu.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
|
283 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldlu(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.lu.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
284 |
+
#else // 32 bits
|
285 |
+
__SM_32_INTRINSICS_DECL__ long __ldlu(const long *ptr) { unsigned long ret; asm ("ld.global.lu.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
|
286 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldlu(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.lu.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
287 |
+
#endif
|
288 |
+
|
289 |
+
|
290 |
+
__SM_32_INTRINSICS_DECL__ char __ldlu(const char *ptr) { unsigned int ret; asm ("ld.global.lu.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (char)ret; }
|
291 |
+
__SM_32_INTRINSICS_DECL__ signed char __ldlu(const signed char *ptr) { unsigned int ret; asm ("ld.global.lu.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (signed char)ret; }
|
292 |
+
__SM_32_INTRINSICS_DECL__ short __ldlu(const short *ptr) { unsigned short ret; asm ("ld.global.lu.s16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return (short)ret; }
|
293 |
+
__SM_32_INTRINSICS_DECL__ int __ldlu(const int *ptr) { unsigned int ret; asm ("ld.global.lu.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (int)ret; }
|
294 |
+
__SM_32_INTRINSICS_DECL__ long long __ldlu(const long long *ptr) { unsigned long long ret; asm ("ld.global.lu.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long long)ret; }
|
295 |
+
__SM_32_INTRINSICS_DECL__ char2 __ldlu(const char2 *ptr) { char2 ret; int2 tmp; asm ("ld.global.lu.v2.s8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
|
296 |
+
__SM_32_INTRINSICS_DECL__ char4 __ldlu(const char4 *ptr) { char4 ret; int4 tmp; asm ("ld.global.lu.v4.s8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
|
297 |
+
__SM_32_INTRINSICS_DECL__ short2 __ldlu(const short2 *ptr) { short2 ret; asm ("ld.global.lu.v2.s16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
298 |
+
__SM_32_INTRINSICS_DECL__ short4 __ldlu(const short4 *ptr) { short4 ret; asm ("ld.global.lu.v4.s16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
299 |
+
__SM_32_INTRINSICS_DECL__ int2 __ldlu(const int2 *ptr) { int2 ret; asm ("ld.global.lu.v2.s32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
300 |
+
__SM_32_INTRINSICS_DECL__ int4 __ldlu(const int4 *ptr) { int4 ret; asm ("ld.global.lu.v4.s32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
301 |
+
__SM_32_INTRINSICS_DECL__ longlong2 __ldlu(const longlong2 *ptr) { longlong2 ret; asm ("ld.global.lu.v2.s64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
302 |
+
|
303 |
+
__SM_32_INTRINSICS_DECL__ unsigned char __ldlu(const unsigned char *ptr) { unsigned int ret; asm ("ld.global.lu.u8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (unsigned char)ret; }
|
304 |
+
__SM_32_INTRINSICS_DECL__ unsigned short __ldlu(const unsigned short *ptr) { unsigned short ret; asm ("ld.global.lu.u16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
305 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __ldlu(const unsigned int *ptr) { unsigned int ret; asm ("ld.global.lu.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
306 |
+
__SM_32_INTRINSICS_DECL__ unsigned long long __ldlu(const unsigned long long *ptr) { unsigned long long ret; asm ("ld.global.lu.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
307 |
+
__SM_32_INTRINSICS_DECL__ uchar2 __ldlu(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm ("ld.global.lu.v2.u8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
|
308 |
+
__SM_32_INTRINSICS_DECL__ uchar4 __ldlu(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm ("ld.global.lu.v4.u8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
|
309 |
+
__SM_32_INTRINSICS_DECL__ ushort2 __ldlu(const ushort2 *ptr) { ushort2 ret; asm ("ld.global.lu.v2.u16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
310 |
+
__SM_32_INTRINSICS_DECL__ ushort4 __ldlu(const ushort4 *ptr) { ushort4 ret; asm ("ld.global.lu.v4.u16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
311 |
+
__SM_32_INTRINSICS_DECL__ uint2 __ldlu(const uint2 *ptr) { uint2 ret; asm ("ld.global.lu.v2.u32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
312 |
+
__SM_32_INTRINSICS_DECL__ uint4 __ldlu(const uint4 *ptr) { uint4 ret; asm ("ld.global.lu.v4.u32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
313 |
+
__SM_32_INTRINSICS_DECL__ ulonglong2 __ldlu(const ulonglong2 *ptr) { ulonglong2 ret; asm ("ld.global.lu.v2.u64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
314 |
+
|
315 |
+
__SM_32_INTRINSICS_DECL__ float __ldlu(const float *ptr) { float ret; asm ("ld.global.lu.f32 %0, [%1];" : "=f"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
316 |
+
__SM_32_INTRINSICS_DECL__ double __ldlu(const double *ptr) { double ret; asm ("ld.global.lu.f64 %0, [%1];" : "=d"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
317 |
+
__SM_32_INTRINSICS_DECL__ float2 __ldlu(const float2 *ptr) { float2 ret; asm ("ld.global.lu.v2.f32 {%0,%1}, [%2];" : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
318 |
+
__SM_32_INTRINSICS_DECL__ float4 __ldlu(const float4 *ptr) { float4 ret; asm ("ld.global.lu.v4.f32 {%0,%1,%2,%3}, [%4];" : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
319 |
+
__SM_32_INTRINSICS_DECL__ double2 __ldlu(const double2 *ptr) { double2 ret; asm ("ld.global.lu.v2.f64 {%0,%1}, [%2];" : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
320 |
+
|
321 |
+
/******************************************************************************
|
322 |
+
* __ldcv *
|
323 |
+
******************************************************************************/
|
324 |
+
|
325 |
+
// Size of long is architecture and OS specific.
|
326 |
+
#if defined(__LP64__) // 64 bits
|
327 |
+
__SM_32_INTRINSICS_DECL__ long __ldcv(const long *ptr) { unsigned long ret; asm ("ld.global.cv.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
|
328 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldcv(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.cv.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
329 |
+
#else // 32 bits
|
330 |
+
__SM_32_INTRINSICS_DECL__ long __ldcv(const long *ptr) { unsigned long ret; asm ("ld.global.cv.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (long)ret; }
|
331 |
+
__SM_32_INTRINSICS_DECL__ unsigned long __ldcv(const unsigned long *ptr) { unsigned long ret; asm ("ld.global.cv.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
332 |
+
#endif
|
333 |
+
|
334 |
+
|
335 |
+
__SM_32_INTRINSICS_DECL__ char __ldcv(const char *ptr) { unsigned int ret; asm ("ld.global.cv.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (char)ret; }
|
336 |
+
__SM_32_INTRINSICS_DECL__ signed char __ldcv(const signed char *ptr) { unsigned int ret; asm ("ld.global.cv.s8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (signed char)ret; }
|
337 |
+
__SM_32_INTRINSICS_DECL__ short __ldcv(const short *ptr) { unsigned short ret; asm ("ld.global.cv.s16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return (short)ret; }
|
338 |
+
__SM_32_INTRINSICS_DECL__ int __ldcv(const int *ptr) { unsigned int ret; asm ("ld.global.cv.s32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (int)ret; }
|
339 |
+
__SM_32_INTRINSICS_DECL__ long long __ldcv(const long long *ptr) { unsigned long long ret; asm ("ld.global.cv.s64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return (long long)ret; }
|
340 |
+
__SM_32_INTRINSICS_DECL__ char2 __ldcv(const char2 *ptr) { char2 ret; int2 tmp; asm ("ld.global.cv.v2.s8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; return ret; }
|
341 |
+
__SM_32_INTRINSICS_DECL__ char4 __ldcv(const char4 *ptr) { char4 ret; int4 tmp; asm ("ld.global.cv.v4.s8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (char)tmp.x; ret.y = (char)tmp.y; ret.z = (char)tmp.z; ret.w = (char)tmp.w; return ret; }
|
342 |
+
__SM_32_INTRINSICS_DECL__ short2 __ldcv(const short2 *ptr) { short2 ret; asm ("ld.global.cv.v2.s16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
343 |
+
__SM_32_INTRINSICS_DECL__ short4 __ldcv(const short4 *ptr) { short4 ret; asm ("ld.global.cv.v4.s16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
344 |
+
__SM_32_INTRINSICS_DECL__ int2 __ldcv(const int2 *ptr) { int2 ret; asm ("ld.global.cv.v2.s32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
345 |
+
__SM_32_INTRINSICS_DECL__ int4 __ldcv(const int4 *ptr) { int4 ret; asm ("ld.global.cv.v4.s32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
346 |
+
__SM_32_INTRINSICS_DECL__ longlong2 __ldcv(const longlong2 *ptr) { longlong2 ret; asm ("ld.global.cv.v2.s64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
347 |
+
|
348 |
+
__SM_32_INTRINSICS_DECL__ unsigned char __ldcv(const unsigned char *ptr) { unsigned int ret; asm ("ld.global.cv.u8 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return (unsigned char)ret; }
|
349 |
+
__SM_32_INTRINSICS_DECL__ unsigned short __ldcv(const unsigned short *ptr) { unsigned short ret; asm ("ld.global.cv.u16 %0, [%1];" : "=h"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
350 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __ldcv(const unsigned int *ptr) { unsigned int ret; asm ("ld.global.cv.u32 %0, [%1];" : "=r"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
351 |
+
__SM_32_INTRINSICS_DECL__ unsigned long long __ldcv(const unsigned long long *ptr) { unsigned long long ret; asm ("ld.global.cv.u64 %0, [%1];" : "=l"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
352 |
+
__SM_32_INTRINSICS_DECL__ uchar2 __ldcv(const uchar2 *ptr) { uchar2 ret; uint2 tmp; asm ("ld.global.cv.v2.u8 {%0,%1}, [%2];" : "=r"(tmp.x), "=r"(tmp.y) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; return ret; }
|
353 |
+
__SM_32_INTRINSICS_DECL__ uchar4 __ldcv(const uchar4 *ptr) { uchar4 ret; uint4 tmp; asm ("ld.global.cv.v4.u8 {%0,%1,%2,%3}, [%4];" : "=r"(tmp.x), "=r"(tmp.y), "=r"(tmp.z), "=r"(tmp.w) : __LDG_PTR (ptr) : "memory"); ret.x = (unsigned char)tmp.x; ret.y = (unsigned char)tmp.y; ret.z = (unsigned char)tmp.z; ret.w = (unsigned char)tmp.w; return ret; }
|
354 |
+
__SM_32_INTRINSICS_DECL__ ushort2 __ldcv(const ushort2 *ptr) { ushort2 ret; asm ("ld.global.cv.v2.u16 {%0,%1}, [%2];" : "=h"(ret.x), "=h"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
355 |
+
__SM_32_INTRINSICS_DECL__ ushort4 __ldcv(const ushort4 *ptr) { ushort4 ret; asm ("ld.global.cv.v4.u16 {%0,%1,%2,%3}, [%4];" : "=h"(ret.x), "=h"(ret.y), "=h"(ret.z), "=h"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
356 |
+
__SM_32_INTRINSICS_DECL__ uint2 __ldcv(const uint2 *ptr) { uint2 ret; asm ("ld.global.cv.v2.u32 {%0,%1}, [%2];" : "=r"(ret.x), "=r"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
357 |
+
__SM_32_INTRINSICS_DECL__ uint4 __ldcv(const uint4 *ptr) { uint4 ret; asm ("ld.global.cv.v4.u32 {%0,%1,%2,%3}, [%4];" : "=r"(ret.x), "=r"(ret.y), "=r"(ret.z), "=r"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
358 |
+
__SM_32_INTRINSICS_DECL__ ulonglong2 __ldcv(const ulonglong2 *ptr) { ulonglong2 ret; asm ("ld.global.cv.v2.u64 {%0,%1}, [%2];" : "=l"(ret.x), "=l"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
359 |
+
|
360 |
+
__SM_32_INTRINSICS_DECL__ float __ldcv(const float *ptr) { float ret; asm ("ld.global.cv.f32 %0, [%1];" : "=f"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
361 |
+
__SM_32_INTRINSICS_DECL__ double __ldcv(const double *ptr) { double ret; asm ("ld.global.cv.f64 %0, [%1];" : "=d"(ret) : __LDG_PTR (ptr) : "memory"); return ret; }
|
362 |
+
__SM_32_INTRINSICS_DECL__ float2 __ldcv(const float2 *ptr) { float2 ret; asm ("ld.global.cv.v2.f32 {%0,%1}, [%2];" : "=f"(ret.x), "=f"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
363 |
+
__SM_32_INTRINSICS_DECL__ float4 __ldcv(const float4 *ptr) { float4 ret; asm ("ld.global.cv.v4.f32 {%0,%1,%2,%3}, [%4];" : "=f"(ret.x), "=f"(ret.y), "=f"(ret.z), "=f"(ret.w) : __LDG_PTR (ptr) : "memory"); return ret; }
|
364 |
+
__SM_32_INTRINSICS_DECL__ double2 __ldcv(const double2 *ptr) { double2 ret; asm ("ld.global.cv.v2.f64 {%0,%1}, [%2];" : "=d"(ret.x), "=d"(ret.y) : __LDG_PTR (ptr) : "memory"); return ret; }
|
365 |
+
|
366 |
+
/******************************************************************************
|
367 |
+
* __stwb *
|
368 |
+
******************************************************************************/
|
369 |
+
|
370 |
+
// Size of long is architecture and OS specific.
|
371 |
+
#if defined(__LP64__) // 64 bits
|
372 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(long *ptr, long value) { asm ("st.global.wb.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
373 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(unsigned long *ptr, unsigned long value) { asm ("st.global.wb.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
374 |
+
#else // 32 bits
|
375 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(long *ptr, long value) { asm ("st.global.wb.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
376 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(unsigned long *ptr, unsigned long value) { asm ("st.global.wb.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
377 |
+
#endif
|
378 |
+
|
379 |
+
|
380 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(char *ptr, char value) { asm ("st.global.wb.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
381 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(signed char *ptr, signed char value) { asm ("st.global.wb.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
382 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(short *ptr, short value) { asm ("st.global.wb.s16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
383 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(int *ptr, int value) { asm ("st.global.wb.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
384 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(long long *ptr, long long value) { asm ("st.global.wb.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
385 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.wb.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
386 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wb.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
387 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(short2 *ptr, short2 value) { asm ("st.global.wb.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
388 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(short4 *ptr, short4 value) { asm ("st.global.wb.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
389 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(int2 *ptr, int2 value) { asm ("st.global.wb.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
390 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(int4 *ptr, int4 value) { asm ("st.global.wb.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
391 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(longlong2 *ptr, longlong2 value) { asm ("st.global.wb.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
392 |
+
|
393 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(unsigned char *ptr, unsigned char value) { asm ("st.global.wb.u8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
394 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(unsigned short *ptr, unsigned short value) { asm ("st.global.wb.u16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
395 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(unsigned int *ptr, unsigned int value) { asm ("st.global.wb.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
396 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(unsigned long long *ptr, unsigned long long value) { asm ("st.global.wb.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
397 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.wb.v2.u8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
398 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wb.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
399 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(ushort2 *ptr, ushort2 value) { asm ("st.global.wb.v2.u16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
400 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(ushort4 *ptr, ushort4 value) { asm ("st.global.wb.v4.u16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
401 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(uint2 *ptr, uint2 value) { asm ("st.global.wb.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
402 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(uint4 *ptr, uint4 value) { asm ("st.global.wb.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
403 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.wb.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
404 |
+
|
405 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(float *ptr, float value) { asm ("st.global.wb.f32 [%0], %1;" :: __LDG_PTR (ptr), "f"(value) : "memory"); }
|
406 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(double *ptr, double value) { asm ("st.global.wb.f64 [%0], %1;" :: __LDG_PTR (ptr), "d"(value) : "memory"); }
|
407 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(float2 *ptr, float2 value) { asm ("st.global.wb.v2.f32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
|
408 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(float4 *ptr, float4 value) { asm ("st.global.wb.v4.f32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
|
409 |
+
__SM_32_INTRINSICS_DECL__ void __stwb(double2 *ptr, double2 value) { asm ("st.global.wb.v2.f64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
|
410 |
+
|
411 |
+
/******************************************************************************
|
412 |
+
* __stcg *
|
413 |
+
******************************************************************************/
|
414 |
+
|
415 |
+
// Size of long is architecture and OS specific.
|
416 |
+
#if defined(__LP64__) // 64 bits
|
417 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(long *ptr, long value) { asm ("st.global.cg.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
418 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(unsigned long *ptr, unsigned long value) { asm ("st.global.cg.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
419 |
+
#else // 32 bits
|
420 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(long *ptr, long value) { asm ("st.global.cg.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
421 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(unsigned long *ptr, unsigned long value) { asm ("st.global.cg.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
422 |
+
#endif
|
423 |
+
|
424 |
+
|
425 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(char *ptr, char value) { asm ("st.global.cg.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
426 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(signed char *ptr, signed char value) { asm ("st.global.cg.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
427 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(short *ptr, short value) { asm ("st.global.cg.s16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
428 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(int *ptr, int value) { asm ("st.global.cg.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
429 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(long long *ptr, long long value) { asm ("st.global.cg.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
430 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.cg.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
431 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cg.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
432 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(short2 *ptr, short2 value) { asm ("st.global.cg.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
433 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(short4 *ptr, short4 value) { asm ("st.global.cg.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
434 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(int2 *ptr, int2 value) { asm ("st.global.cg.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
435 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(int4 *ptr, int4 value) { asm ("st.global.cg.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
436 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(longlong2 *ptr, longlong2 value) { asm ("st.global.cg.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
437 |
+
|
438 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(unsigned char *ptr, unsigned char value) { asm ("st.global.cg.u8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
439 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(unsigned short *ptr, unsigned short value) { asm ("st.global.cg.u16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
440 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(unsigned int *ptr, unsigned int value) { asm ("st.global.cg.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
441 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(unsigned long long *ptr, unsigned long long value) { asm ("st.global.cg.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
442 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.cg.v2.u8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
443 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cg.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
444 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(ushort2 *ptr, ushort2 value) { asm ("st.global.cg.v2.u16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
445 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(ushort4 *ptr, ushort4 value) { asm ("st.global.cg.v4.u16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
446 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(uint2 *ptr, uint2 value) { asm ("st.global.cg.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
447 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(uint4 *ptr, uint4 value) { asm ("st.global.cg.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
448 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.cg.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
449 |
+
|
450 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(float *ptr, float value) { asm ("st.global.cg.f32 [%0], %1;" :: __LDG_PTR (ptr), "f"(value) : "memory"); }
|
451 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(double *ptr, double value) { asm ("st.global.cg.f64 [%0], %1;" :: __LDG_PTR (ptr), "d"(value) : "memory"); }
|
452 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(float2 *ptr, float2 value) { asm ("st.global.cg.v2.f32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
|
453 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(float4 *ptr, float4 value) { asm ("st.global.cg.v4.f32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
|
454 |
+
__SM_32_INTRINSICS_DECL__ void __stcg(double2 *ptr, double2 value) { asm ("st.global.cg.v2.f64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
|
455 |
+
|
456 |
+
/******************************************************************************
|
457 |
+
* __stcs *
|
458 |
+
******************************************************************************/
|
459 |
+
|
460 |
+
// Size of long is architecture and OS specific.
|
461 |
+
#if defined(__LP64__) // 64 bits
|
462 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(long *ptr, long value) { asm ("st.global.cs.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
463 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(unsigned long *ptr, unsigned long value) { asm ("st.global.cs.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
464 |
+
#else // 32 bits
|
465 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(long *ptr, long value) { asm ("st.global.cs.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
466 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(unsigned long *ptr, unsigned long value) { asm ("st.global.cs.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
467 |
+
#endif
|
468 |
+
|
469 |
+
|
470 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(char *ptr, char value) { asm ("st.global.cs.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
471 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(signed char *ptr, signed char value) { asm ("st.global.cs.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
472 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(short *ptr, short value) { asm ("st.global.cs.s16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
473 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(int *ptr, int value) { asm ("st.global.cs.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
474 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(long long *ptr, long long value) { asm ("st.global.cs.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
475 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.cs.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
476 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cs.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
477 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(short2 *ptr, short2 value) { asm ("st.global.cs.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
478 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(short4 *ptr, short4 value) { asm ("st.global.cs.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
479 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(int2 *ptr, int2 value) { asm ("st.global.cs.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
480 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(int4 *ptr, int4 value) { asm ("st.global.cs.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
481 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(longlong2 *ptr, longlong2 value) { asm ("st.global.cs.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
482 |
+
|
483 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(unsigned char *ptr, unsigned char value) { asm ("st.global.cs.u8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
484 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(unsigned short *ptr, unsigned short value) { asm ("st.global.cs.u16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
485 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(unsigned int *ptr, unsigned int value) { asm ("st.global.cs.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
486 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(unsigned long long *ptr, unsigned long long value) { asm ("st.global.cs.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
487 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.cs.v2.u8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
488 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.cs.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
489 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(ushort2 *ptr, ushort2 value) { asm ("st.global.cs.v2.u16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
490 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(ushort4 *ptr, ushort4 value) { asm ("st.global.cs.v4.u16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
491 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(uint2 *ptr, uint2 value) { asm ("st.global.cs.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
492 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(uint4 *ptr, uint4 value) { asm ("st.global.cs.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
493 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.cs.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
494 |
+
|
495 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(float *ptr, float value) { asm ("st.global.cs.f32 [%0], %1;" :: __LDG_PTR (ptr), "f"(value) : "memory"); }
|
496 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(double *ptr, double value) { asm ("st.global.cs.f64 [%0], %1;" :: __LDG_PTR (ptr), "d"(value) : "memory"); }
|
497 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(float2 *ptr, float2 value) { asm ("st.global.cs.v2.f32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
|
498 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(float4 *ptr, float4 value) { asm ("st.global.cs.v4.f32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
|
499 |
+
__SM_32_INTRINSICS_DECL__ void __stcs(double2 *ptr, double2 value) { asm ("st.global.cs.v2.f64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
|
500 |
+
|
501 |
+
/******************************************************************************
|
502 |
+
* __stwt *
|
503 |
+
******************************************************************************/
|
504 |
+
|
505 |
+
// Size of long is architecture and OS specific.
|
506 |
+
#if defined(__LP64__) // 64 bits
|
507 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(long *ptr, long value) { asm ("st.global.wt.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
508 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(unsigned long *ptr, unsigned long value) { asm ("st.global.wt.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
509 |
+
#else // 32 bits
|
510 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(long *ptr, long value) { asm ("st.global.wt.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
511 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(unsigned long *ptr, unsigned long value) { asm ("st.global.wt.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
512 |
+
#endif
|
513 |
+
|
514 |
+
|
515 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(char *ptr, char value) { asm ("st.global.wt.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
516 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(signed char *ptr, signed char value) { asm ("st.global.wt.s8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
517 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(short *ptr, short value) { asm ("st.global.wt.s16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
518 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(int *ptr, int value) { asm ("st.global.wt.s32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
519 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(long long *ptr, long long value) { asm ("st.global.wt.s64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
520 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(char2 *ptr, char2 value) { const int x = value.x, y = value.y; asm ("st.global.wt.v2.s8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
521 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(char4 *ptr, char4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wt.v4.s8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
522 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(short2 *ptr, short2 value) { asm ("st.global.wt.v2.s16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
523 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(short4 *ptr, short4 value) { asm ("st.global.wt.v4.s16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
524 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(int2 *ptr, int2 value) { asm ("st.global.wt.v2.s32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
525 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(int4 *ptr, int4 value) { asm ("st.global.wt.v4.s32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
526 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(longlong2 *ptr, longlong2 value) { asm ("st.global.wt.v2.s64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
527 |
+
|
528 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(unsigned char *ptr, unsigned char value) { asm ("st.global.wt.u8 [%0], %1;" :: __LDG_PTR (ptr), "r"((int)value) : "memory"); }
|
529 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(unsigned short *ptr, unsigned short value) { asm ("st.global.wt.u16 [%0], %1;" :: __LDG_PTR (ptr), "h"(value) : "memory"); }
|
530 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(unsigned int *ptr, unsigned int value) { asm ("st.global.wt.u32 [%0], %1;" :: __LDG_PTR (ptr), "r"(value) : "memory"); }
|
531 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(unsigned long long *ptr, unsigned long long value) { asm ("st.global.wt.u64 [%0], %1;" :: __LDG_PTR (ptr), "l"(value) : "memory"); }
|
532 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(uchar2 *ptr, uchar2 value) { const int x = value.x, y = value.y; asm ("st.global.wt.v2.u8 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(x), "r"(y) : "memory"); }
|
533 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(uchar4 *ptr, uchar4 value) { const int x = value.x, y = value.y, z = value.z, w = value.w; asm ("st.global.wt.v4.u8 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(x), "r"(y), "r"(z), "r"(w) : "memory"); }
|
534 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(ushort2 *ptr, ushort2 value) { asm ("st.global.wt.v2.u16 [%0], {%1,%2};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y) : "memory"); }
|
535 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(ushort4 *ptr, ushort4 value) { asm ("st.global.wt.v4.u16 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "h"(value.x), "h"(value.y), "h"(value.z), "h"(value.w) : "memory"); }
|
536 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(uint2 *ptr, uint2 value) { asm ("st.global.wt.v2.u32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y) : "memory"); }
|
537 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(uint4 *ptr, uint4 value) { asm ("st.global.wt.v4.u32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "r"(value.x), "r"(value.y), "r"(value.z), "r"(value.w) : "memory"); }
|
538 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(ulonglong2 *ptr, ulonglong2 value) { asm ("st.global.wt.v2.u64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "l"(value.x), "l"(value.y) : "memory"); }
|
539 |
+
|
540 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(float *ptr, float value) { asm ("st.global.wt.f32 [%0], %1;" :: __LDG_PTR (ptr), "f"(value) : "memory"); }
|
541 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(double *ptr, double value) { asm ("st.global.wt.f64 [%0], %1;" :: __LDG_PTR (ptr), "d"(value) : "memory"); }
|
542 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(float2 *ptr, float2 value) { asm ("st.global.wt.v2.f32 [%0], {%1,%2};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y) : "memory"); }
|
543 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(float4 *ptr, float4 value) { asm ("st.global.wt.v4.f32 [%0], {%1,%2,%3,%4};" :: __LDG_PTR (ptr), "f"(value.x), "f"(value.y), "f"(value.z), "f"(value.w) : "memory"); }
|
544 |
+
__SM_32_INTRINSICS_DECL__ void __stwt(double2 *ptr, double2 value) { asm ("st.global.wt.v2.f64 [%0], {%1,%2};" :: __LDG_PTR (ptr), "d"(value.x), "d"(value.y) : "memory"); }
|
545 |
+
|
546 |
+
#undef __LDG_PTR
|
547 |
+
|
548 |
+
|
549 |
+
// SHF is the "funnel shift" operation - an accelerated left/right shift with carry
|
550 |
+
// operating on 64-bit quantities, which are concatenations of two 32-bit registers.
|
551 |
+
|
552 |
+
// This shifts [b:a] left by "shift" bits, returning the most significant bits of the result.
|
553 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_l(unsigned int lo, unsigned int hi, unsigned int shift)
|
554 |
+
{
|
555 |
+
unsigned int ret;
|
556 |
+
asm volatile ("shf.l.wrap.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
|
557 |
+
return ret;
|
558 |
+
}
|
559 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_lc(unsigned int lo, unsigned int hi, unsigned int shift)
|
560 |
+
{
|
561 |
+
unsigned int ret;
|
562 |
+
asm volatile ("shf.l.clamp.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
|
563 |
+
return ret;
|
564 |
+
}
|
565 |
+
|
566 |
+
// This shifts [b:a] right by "shift" bits, returning the least significant bits of the result.
|
567 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_r(unsigned int lo, unsigned int hi, unsigned int shift)
|
568 |
+
{
|
569 |
+
unsigned int ret;
|
570 |
+
asm volatile ("shf.r.wrap.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
|
571 |
+
return ret;
|
572 |
+
}
|
573 |
+
__SM_32_INTRINSICS_DECL__ unsigned int __funnelshift_rc(unsigned int lo, unsigned int hi, unsigned int shift)
|
574 |
+
{
|
575 |
+
unsigned int ret;
|
576 |
+
asm volatile ("shf.r.clamp.b32 %0, %1, %2, %3;" : "=r"(ret) : "r"(lo), "r"(hi), "r"(shift));
|
577 |
+
return ret;
|
578 |
+
}
|
579 |
+
|
580 |
+
|
581 |
+
#endif /* _NVHPC_CUDA || !__CUDA_ARCH__ || __CUDA_ARCH__ >= 320 */
|
582 |
+
|
583 |
+
#endif /* __cplusplus && __CUDACC__ */
|
584 |
+
|
585 |
+
#undef __SM_32_INTRINSICS_DECL__
|
586 |
+
|
587 |
+
#endif /* !__SM_32_INTRINSICS_HPP__ */
|
588 |
+
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/surface_functions.h
ADDED
@@ -0,0 +1,124 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2022 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__SURFACE_FUNCTIONS_H__)
|
51 |
+
#define __SURFACE_FUNCTIONS_H__
|
52 |
+
|
53 |
+
|
54 |
+
#if defined(__cplusplus) && defined(__CUDACC__)
|
55 |
+
|
56 |
+
/*******************************************************************************
|
57 |
+
* *
|
58 |
+
* *
|
59 |
+
* *
|
60 |
+
*******************************************************************************/
|
61 |
+
|
62 |
+
#include "cuda_runtime_api.h"
|
63 |
+
#include "cuda_surface_types.h"
|
64 |
+
|
65 |
+
#if defined(_WIN32)
|
66 |
+
# define __DEPRECATED__ __declspec(deprecated)
|
67 |
+
#else
|
68 |
+
# define __DEPRECATED__ __attribute__((deprecated))
|
69 |
+
#endif
|
70 |
+
|
71 |
+
template <typename T> struct __nv_surf_trait { typedef void * cast_type; };
|
72 |
+
|
73 |
+
template<> struct __nv_surf_trait<char> { typedef char * cast_type; };
|
74 |
+
template<> struct __nv_surf_trait<signed char> { typedef signed char * cast_type; };
|
75 |
+
template<> struct __nv_surf_trait<unsigned char> { typedef unsigned char * cast_type; };
|
76 |
+
template<> struct __nv_surf_trait<char1> { typedef char1 * cast_type; };
|
77 |
+
template<> struct __nv_surf_trait<uchar1> { typedef uchar1 * cast_type; };
|
78 |
+
template<> struct __nv_surf_trait<char2> { typedef char2 * cast_type; };
|
79 |
+
template<> struct __nv_surf_trait<uchar2> { typedef uchar2 * cast_type; };
|
80 |
+
template<> struct __nv_surf_trait<char4> { typedef char4 * cast_type; };
|
81 |
+
template<> struct __nv_surf_trait<uchar4> { typedef uchar4 * cast_type; };
|
82 |
+
template<> struct __nv_surf_trait<short> { typedef short * cast_type; };
|
83 |
+
template<> struct __nv_surf_trait<unsigned short> { typedef unsigned short * cast_type; };
|
84 |
+
template<> struct __nv_surf_trait<short1> { typedef short1 * cast_type; };
|
85 |
+
template<> struct __nv_surf_trait<ushort1> { typedef ushort1 * cast_type; };
|
86 |
+
template<> struct __nv_surf_trait<short2> { typedef short2 * cast_type; };
|
87 |
+
template<> struct __nv_surf_trait<ushort2> { typedef ushort2 * cast_type; };
|
88 |
+
template<> struct __nv_surf_trait<short4> { typedef short4 * cast_type; };
|
89 |
+
template<> struct __nv_surf_trait<ushort4> { typedef ushort4 * cast_type; };
|
90 |
+
template<> struct __nv_surf_trait<int> { typedef int * cast_type; };
|
91 |
+
template<> struct __nv_surf_trait<unsigned int> { typedef unsigned int * cast_type; };
|
92 |
+
template<> struct __nv_surf_trait<int1> { typedef int1 * cast_type; };
|
93 |
+
template<> struct __nv_surf_trait<uint1> { typedef uint1 * cast_type; };
|
94 |
+
template<> struct __nv_surf_trait<int2> { typedef int2 * cast_type; };
|
95 |
+
template<> struct __nv_surf_trait<uint2> { typedef uint2 * cast_type; };
|
96 |
+
template<> struct __nv_surf_trait<int4> { typedef int4 * cast_type; };
|
97 |
+
template<> struct __nv_surf_trait<uint4> { typedef uint4 * cast_type; };
|
98 |
+
template<> struct __nv_surf_trait<long long> { typedef long long * cast_type; };
|
99 |
+
template<> struct __nv_surf_trait<unsigned long long> { typedef unsigned long long * cast_type; };
|
100 |
+
template<> struct __nv_surf_trait<longlong1> { typedef longlong1 * cast_type; };
|
101 |
+
template<> struct __nv_surf_trait<ulonglong1> { typedef ulonglong1 * cast_type; };
|
102 |
+
template<> struct __nv_surf_trait<longlong2> { typedef longlong2 * cast_type; };
|
103 |
+
template<> struct __nv_surf_trait<ulonglong2> { typedef ulonglong2 * cast_type; };
|
104 |
+
#if !defined(__LP64__)
|
105 |
+
template<> struct __nv_surf_trait<long> { typedef int * cast_type; };
|
106 |
+
template<> struct __nv_surf_trait<unsigned long> { typedef unsigned int * cast_type; };
|
107 |
+
template<> struct __nv_surf_trait<long1> { typedef int1 * cast_type; };
|
108 |
+
template<> struct __nv_surf_trait<ulong1> { typedef uint1 * cast_type; };
|
109 |
+
template<> struct __nv_surf_trait<long2> { typedef int2 * cast_type; };
|
110 |
+
template<> struct __nv_surf_trait<ulong2> { typedef uint2 * cast_type; };
|
111 |
+
template<> struct __nv_surf_trait<long4> { typedef uint4 * cast_type; };
|
112 |
+
template<> struct __nv_surf_trait<ulong4> { typedef int4 * cast_type; };
|
113 |
+
#endif
|
114 |
+
template<> struct __nv_surf_trait<float> { typedef float * cast_type; };
|
115 |
+
template<> struct __nv_surf_trait<float1> { typedef float1 * cast_type; };
|
116 |
+
template<> struct __nv_surf_trait<float2> { typedef float2 * cast_type; };
|
117 |
+
template<> struct __nv_surf_trait<float4> { typedef float4 * cast_type; };
|
118 |
+
|
119 |
+
|
120 |
+
#undef __DEPRECATED__
|
121 |
+
|
122 |
+
|
123 |
+
#endif /* __cplusplus && __CUDACC__ */
|
124 |
+
#endif /* !__SURFACE_FUNCTIONS_H__ */
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/texture_indirect_functions.h
ADDED
@@ -0,0 +1,638 @@
|
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|
|
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|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2022 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
|
51 |
+
#ifndef __TEXTURE_INDIRECT_FUNCTIONS_H__
|
52 |
+
#define __TEXTURE_INDIRECT_FUNCTIONS_H__
|
53 |
+
|
54 |
+
|
55 |
+
#if defined(__cplusplus) && defined(__CUDACC__)
|
56 |
+
|
57 |
+
|
58 |
+
#include "cuda_runtime_api.h"
|
59 |
+
|
60 |
+
|
61 |
+
#if defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 600)
|
62 |
+
#define __NV_TEX_SPARSE 1
|
63 |
+
#endif /* endif */
|
64 |
+
|
65 |
+
template <typename T> struct __nv_itex_trait { };
|
66 |
+
template<> struct __nv_itex_trait<char> { typedef void type; };
|
67 |
+
template<> struct __nv_itex_trait<signed char> { typedef void type; };
|
68 |
+
template<> struct __nv_itex_trait<char1> { typedef void type; };
|
69 |
+
template<> struct __nv_itex_trait<char2> { typedef void type; };
|
70 |
+
template<> struct __nv_itex_trait<char4> { typedef void type; };
|
71 |
+
template<> struct __nv_itex_trait<unsigned char> { typedef void type; };
|
72 |
+
template<> struct __nv_itex_trait<uchar1> { typedef void type; };
|
73 |
+
template<> struct __nv_itex_trait<uchar2> { typedef void type; };
|
74 |
+
template<> struct __nv_itex_trait<uchar4> { typedef void type; };
|
75 |
+
template<> struct __nv_itex_trait<short> { typedef void type; };
|
76 |
+
template<> struct __nv_itex_trait<short1> { typedef void type; };
|
77 |
+
template<> struct __nv_itex_trait<short2> { typedef void type; };
|
78 |
+
template<> struct __nv_itex_trait<short4> { typedef void type; };
|
79 |
+
template<> struct __nv_itex_trait<unsigned short> { typedef void type; };
|
80 |
+
template<> struct __nv_itex_trait<ushort1> { typedef void type; };
|
81 |
+
template<> struct __nv_itex_trait<ushort2> { typedef void type; };
|
82 |
+
template<> struct __nv_itex_trait<ushort4> { typedef void type; };
|
83 |
+
template<> struct __nv_itex_trait<int> { typedef void type; };
|
84 |
+
template<> struct __nv_itex_trait<int1> { typedef void type; };
|
85 |
+
template<> struct __nv_itex_trait<int2> { typedef void type; };
|
86 |
+
template<> struct __nv_itex_trait<int4> { typedef void type; };
|
87 |
+
template<> struct __nv_itex_trait<unsigned int> { typedef void type; };
|
88 |
+
template<> struct __nv_itex_trait<uint1> { typedef void type; };
|
89 |
+
template<> struct __nv_itex_trait<uint2> { typedef void type; };
|
90 |
+
template<> struct __nv_itex_trait<uint4> { typedef void type; };
|
91 |
+
#if !defined(__LP64__)
|
92 |
+
template<> struct __nv_itex_trait<long> { typedef void type; };
|
93 |
+
template<> struct __nv_itex_trait<long1> { typedef void type; };
|
94 |
+
template<> struct __nv_itex_trait<long2> { typedef void type; };
|
95 |
+
template<> struct __nv_itex_trait<long4> { typedef void type; };
|
96 |
+
template<> struct __nv_itex_trait<unsigned long> { typedef void type; };
|
97 |
+
template<> struct __nv_itex_trait<ulong1> { typedef void type; };
|
98 |
+
template<> struct __nv_itex_trait<ulong2> { typedef void type; };
|
99 |
+
template<> struct __nv_itex_trait<ulong4> { typedef void type; };
|
100 |
+
#endif /* !__LP64__ */
|
101 |
+
template<> struct __nv_itex_trait<float> { typedef void type; };
|
102 |
+
template<> struct __nv_itex_trait<float1> { typedef void type; };
|
103 |
+
template<> struct __nv_itex_trait<float2> { typedef void type; };
|
104 |
+
template<> struct __nv_itex_trait<float4> { typedef void type; };
|
105 |
+
|
106 |
+
|
107 |
+
|
108 |
+
template <typename T>
|
109 |
+
static __device__ typename __nv_itex_trait<T>::type tex1Dfetch(T *ptr, cudaTextureObject_t obj, int x)
|
110 |
+
{
|
111 |
+
__nv_tex_surf_handler("__itex1Dfetch", ptr, obj, x);
|
112 |
+
}
|
113 |
+
|
114 |
+
template <class T>
|
115 |
+
static __device__ T tex1Dfetch(cudaTextureObject_t texObject, int x)
|
116 |
+
{
|
117 |
+
T ret;
|
118 |
+
tex1Dfetch(&ret, texObject, x);
|
119 |
+
return ret;
|
120 |
+
}
|
121 |
+
|
122 |
+
template <typename T>
|
123 |
+
static __device__ typename __nv_itex_trait<T>::type tex1D(T *ptr, cudaTextureObject_t obj, float x)
|
124 |
+
{
|
125 |
+
__nv_tex_surf_handler("__itex1D", ptr, obj, x);
|
126 |
+
}
|
127 |
+
|
128 |
+
|
129 |
+
template <class T>
|
130 |
+
static __device__ T tex1D(cudaTextureObject_t texObject, float x)
|
131 |
+
{
|
132 |
+
T ret;
|
133 |
+
tex1D(&ret, texObject, x);
|
134 |
+
return ret;
|
135 |
+
}
|
136 |
+
|
137 |
+
|
138 |
+
template <typename T>
|
139 |
+
static __device__ typename __nv_itex_trait<T>::type tex2D(T *ptr, cudaTextureObject_t obj, float x, float y)
|
140 |
+
{
|
141 |
+
__nv_tex_surf_handler("__itex2D", ptr, obj, x, y);
|
142 |
+
}
|
143 |
+
|
144 |
+
template <class T>
|
145 |
+
static __device__ T tex2D(cudaTextureObject_t texObject, float x, float y)
|
146 |
+
{
|
147 |
+
T ret;
|
148 |
+
tex2D(&ret, texObject, x, y);
|
149 |
+
return ret;
|
150 |
+
}
|
151 |
+
|
152 |
+
#if __NV_TEX_SPARSE
|
153 |
+
template <typename T>
|
154 |
+
static __device__ typename __nv_itex_trait<T>::type tex2D(T *ptr, cudaTextureObject_t obj, float x, float y,
|
155 |
+
bool* isResident)
|
156 |
+
{
|
157 |
+
unsigned char res;
|
158 |
+
__nv_tex_surf_handler("__itex2D_sparse", ptr, obj, x, y, &res);
|
159 |
+
*isResident = (res != 0);
|
160 |
+
}
|
161 |
+
|
162 |
+
template <class T>
|
163 |
+
static __device__ T tex2D(cudaTextureObject_t texObject, float x, float y, bool* isResident)
|
164 |
+
{
|
165 |
+
T ret;
|
166 |
+
tex2D(&ret, texObject, x, y, isResident);
|
167 |
+
return ret;
|
168 |
+
}
|
169 |
+
|
170 |
+
#endif /* __NV_TEX_SPARSE */
|
171 |
+
|
172 |
+
|
173 |
+
template <typename T>
|
174 |
+
static __device__ typename __nv_itex_trait<T>::type tex3D(T *ptr, cudaTextureObject_t obj, float x, float y, float z)
|
175 |
+
{
|
176 |
+
__nv_tex_surf_handler("__itex3D", ptr, obj, x, y, z);
|
177 |
+
}
|
178 |
+
|
179 |
+
template <class T>
|
180 |
+
static __device__ T tex3D(cudaTextureObject_t texObject, float x, float y, float z)
|
181 |
+
{
|
182 |
+
T ret;
|
183 |
+
tex3D(&ret, texObject, x, y, z);
|
184 |
+
return ret;
|
185 |
+
}
|
186 |
+
|
187 |
+
#if __NV_TEX_SPARSE
|
188 |
+
template <typename T>
|
189 |
+
static __device__ typename __nv_itex_trait<T>::type tex3D(T *ptr, cudaTextureObject_t obj, float x, float y, float z,
|
190 |
+
bool* isResident)
|
191 |
+
{
|
192 |
+
unsigned char res;
|
193 |
+
__nv_tex_surf_handler("__itex3D_sparse", ptr, obj, x, y, z, &res);
|
194 |
+
*isResident = (res != 0);
|
195 |
+
}
|
196 |
+
|
197 |
+
template <class T>
|
198 |
+
static __device__ T tex3D(cudaTextureObject_t texObject, float x, float y, float z, bool* isResident)
|
199 |
+
{
|
200 |
+
T ret;
|
201 |
+
tex3D(&ret, texObject, x, y, z, isResident);
|
202 |
+
return ret;
|
203 |
+
}
|
204 |
+
#endif /* __NV_TEX_SPARSE */
|
205 |
+
|
206 |
+
|
207 |
+
template <typename T>
|
208 |
+
static __device__ typename __nv_itex_trait<T>::type tex1DLayered(T *ptr, cudaTextureObject_t obj, float x, int layer)
|
209 |
+
{
|
210 |
+
__nv_tex_surf_handler("__itex1DLayered", ptr, obj, x, layer);
|
211 |
+
}
|
212 |
+
|
213 |
+
template <class T>
|
214 |
+
static __device__ T tex1DLayered(cudaTextureObject_t texObject, float x, int layer)
|
215 |
+
{
|
216 |
+
T ret;
|
217 |
+
tex1DLayered(&ret, texObject, x, layer);
|
218 |
+
return ret;
|
219 |
+
}
|
220 |
+
|
221 |
+
template <typename T>
|
222 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLayered(T *ptr, cudaTextureObject_t obj, float x, float y, int layer)
|
223 |
+
{
|
224 |
+
__nv_tex_surf_handler("__itex2DLayered", ptr, obj, x, y, layer);
|
225 |
+
}
|
226 |
+
|
227 |
+
template <class T>
|
228 |
+
static __device__ T tex2DLayered(cudaTextureObject_t texObject, float x, float y, int layer)
|
229 |
+
{
|
230 |
+
T ret;
|
231 |
+
tex2DLayered(&ret, texObject, x, y, layer);
|
232 |
+
return ret;
|
233 |
+
}
|
234 |
+
|
235 |
+
#if __NV_TEX_SPARSE
|
236 |
+
template <typename T>
|
237 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLayered(T *ptr, cudaTextureObject_t obj, float x, float y, int layer, bool* isResident)
|
238 |
+
{
|
239 |
+
unsigned char res;
|
240 |
+
__nv_tex_surf_handler("__itex2DLayered_sparse", ptr, obj, x, y, layer, &res);
|
241 |
+
*isResident = (res != 0);
|
242 |
+
}
|
243 |
+
|
244 |
+
template <class T>
|
245 |
+
static __device__ T tex2DLayered(cudaTextureObject_t texObject, float x, float y, int layer, bool* isResident)
|
246 |
+
{
|
247 |
+
T ret;
|
248 |
+
tex2DLayered(&ret, texObject, x, y, layer, isResident);
|
249 |
+
return ret;
|
250 |
+
}
|
251 |
+
#endif /* __NV_TEX_SPARSE */
|
252 |
+
|
253 |
+
|
254 |
+
template <typename T>
|
255 |
+
static __device__ typename __nv_itex_trait<T>::type texCubemap(T *ptr, cudaTextureObject_t obj, float x, float y, float z)
|
256 |
+
{
|
257 |
+
__nv_tex_surf_handler("__itexCubemap", ptr, obj, x, y, z);
|
258 |
+
}
|
259 |
+
|
260 |
+
|
261 |
+
template <class T>
|
262 |
+
static __device__ T texCubemap(cudaTextureObject_t texObject, float x, float y, float z)
|
263 |
+
{
|
264 |
+
T ret;
|
265 |
+
texCubemap(&ret, texObject, x, y, z);
|
266 |
+
return ret;
|
267 |
+
}
|
268 |
+
|
269 |
+
|
270 |
+
template <typename T>
|
271 |
+
static __device__ typename __nv_itex_trait<T>::type texCubemapLayered(T *ptr, cudaTextureObject_t obj, float x, float y, float z, int layer)
|
272 |
+
{
|
273 |
+
__nv_tex_surf_handler("__itexCubemapLayered", ptr, obj, x, y, z, layer);
|
274 |
+
}
|
275 |
+
|
276 |
+
template <class T>
|
277 |
+
static __device__ T texCubemapLayered(cudaTextureObject_t texObject, float x, float y, float z, int layer)
|
278 |
+
{
|
279 |
+
T ret;
|
280 |
+
texCubemapLayered(&ret, texObject, x, y, z, layer);
|
281 |
+
return ret;
|
282 |
+
}
|
283 |
+
|
284 |
+
template <typename T>
|
285 |
+
static __device__ typename __nv_itex_trait<T>::type tex2Dgather(T *ptr, cudaTextureObject_t obj, float x, float y, int comp = 0)
|
286 |
+
{
|
287 |
+
__nv_tex_surf_handler("__itex2Dgather", ptr, obj, x, y, comp);
|
288 |
+
}
|
289 |
+
|
290 |
+
template <class T>
|
291 |
+
static __device__ T tex2Dgather(cudaTextureObject_t to, float x, float y, int comp = 0)
|
292 |
+
{
|
293 |
+
T ret;
|
294 |
+
tex2Dgather(&ret, to, x, y, comp);
|
295 |
+
return ret;
|
296 |
+
}
|
297 |
+
|
298 |
+
#if __NV_TEX_SPARSE
|
299 |
+
template <typename T>
|
300 |
+
static __device__ typename __nv_itex_trait<T>::type tex2Dgather(T *ptr, cudaTextureObject_t obj, float x, float y, bool* isResident, int comp = 0)
|
301 |
+
{
|
302 |
+
unsigned char res;
|
303 |
+
__nv_tex_surf_handler("__itex2Dgather_sparse", ptr, obj, x, y, comp, &res);
|
304 |
+
*isResident = (res != 0);
|
305 |
+
}
|
306 |
+
|
307 |
+
template <class T>
|
308 |
+
static __device__ T tex2Dgather(cudaTextureObject_t to, float x, float y, bool* isResident, int comp = 0)
|
309 |
+
{
|
310 |
+
T ret;
|
311 |
+
tex2Dgather(&ret, to, x, y, isResident, comp);
|
312 |
+
return ret;
|
313 |
+
}
|
314 |
+
|
315 |
+
#endif /* __NV_TEX_SPARSE */
|
316 |
+
|
317 |
+
template <typename T>
|
318 |
+
static __device__ typename __nv_itex_trait<T>::type tex1DLod(T *ptr, cudaTextureObject_t obj, float x, float level)
|
319 |
+
{
|
320 |
+
__nv_tex_surf_handler("__itex1DLod", ptr, obj, x, level);
|
321 |
+
}
|
322 |
+
|
323 |
+
template <class T>
|
324 |
+
static __device__ T tex1DLod(cudaTextureObject_t texObject, float x, float level)
|
325 |
+
{
|
326 |
+
T ret;
|
327 |
+
tex1DLod(&ret, texObject, x, level);
|
328 |
+
return ret;
|
329 |
+
}
|
330 |
+
|
331 |
+
|
332 |
+
template <typename T>
|
333 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLod(T *ptr, cudaTextureObject_t obj, float x, float y, float level)
|
334 |
+
{
|
335 |
+
__nv_tex_surf_handler("__itex2DLod", ptr, obj, x, y, level);
|
336 |
+
}
|
337 |
+
|
338 |
+
template <class T>
|
339 |
+
static __device__ T tex2DLod(cudaTextureObject_t texObject, float x, float y, float level)
|
340 |
+
{
|
341 |
+
T ret;
|
342 |
+
tex2DLod(&ret, texObject, x, y, level);
|
343 |
+
return ret;
|
344 |
+
}
|
345 |
+
|
346 |
+
#if __NV_TEX_SPARSE
|
347 |
+
|
348 |
+
template <typename T>
|
349 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLod(T *ptr, cudaTextureObject_t obj, float x, float y, float level, bool* isResident)
|
350 |
+
{
|
351 |
+
unsigned char res;
|
352 |
+
__nv_tex_surf_handler("__itex2DLod_sparse", ptr, obj, x, y, level, &res);
|
353 |
+
*isResident = (res != 0);
|
354 |
+
}
|
355 |
+
|
356 |
+
template <class T>
|
357 |
+
static __device__ T tex2DLod(cudaTextureObject_t texObject, float x, float y, float level, bool* isResident)
|
358 |
+
{
|
359 |
+
T ret;
|
360 |
+
tex2DLod(&ret, texObject, x, y, level, isResident);
|
361 |
+
return ret;
|
362 |
+
}
|
363 |
+
|
364 |
+
#endif /* __NV_TEX_SPARSE */
|
365 |
+
|
366 |
+
|
367 |
+
template <typename T>
|
368 |
+
static __device__ typename __nv_itex_trait<T>::type tex3DLod(T *ptr, cudaTextureObject_t obj, float x, float y, float z, float level)
|
369 |
+
{
|
370 |
+
__nv_tex_surf_handler("__itex3DLod", ptr, obj, x, y, z, level);
|
371 |
+
}
|
372 |
+
|
373 |
+
template <class T>
|
374 |
+
static __device__ T tex3DLod(cudaTextureObject_t texObject, float x, float y, float z, float level)
|
375 |
+
{
|
376 |
+
T ret;
|
377 |
+
tex3DLod(&ret, texObject, x, y, z, level);
|
378 |
+
return ret;
|
379 |
+
}
|
380 |
+
|
381 |
+
#if __NV_TEX_SPARSE
|
382 |
+
template <typename T>
|
383 |
+
static __device__ typename __nv_itex_trait<T>::type tex3DLod(T *ptr, cudaTextureObject_t obj, float x, float y, float z, float level, bool* isResident)
|
384 |
+
{
|
385 |
+
unsigned char res;
|
386 |
+
__nv_tex_surf_handler("__itex3DLod_sparse", ptr, obj, x, y, z, level, &res);
|
387 |
+
*isResident = (res != 0);
|
388 |
+
}
|
389 |
+
|
390 |
+
template <class T>
|
391 |
+
static __device__ T tex3DLod(cudaTextureObject_t texObject, float x, float y, float z, float level, bool* isResident)
|
392 |
+
{
|
393 |
+
T ret;
|
394 |
+
tex3DLod(&ret, texObject, x, y, z, level, isResident);
|
395 |
+
return ret;
|
396 |
+
}
|
397 |
+
|
398 |
+
#endif /* __NV_TEX_SPARSE */
|
399 |
+
|
400 |
+
|
401 |
+
template <typename T>
|
402 |
+
static __device__ typename __nv_itex_trait<T>::type tex1DLayeredLod(T *ptr, cudaTextureObject_t obj, float x, int layer, float level)
|
403 |
+
{
|
404 |
+
__nv_tex_surf_handler("__itex1DLayeredLod", ptr, obj, x, layer, level);
|
405 |
+
}
|
406 |
+
|
407 |
+
template <class T>
|
408 |
+
static __device__ T tex1DLayeredLod(cudaTextureObject_t texObject, float x, int layer, float level)
|
409 |
+
{
|
410 |
+
T ret;
|
411 |
+
tex1DLayeredLod(&ret, texObject, x, layer, level);
|
412 |
+
return ret;
|
413 |
+
}
|
414 |
+
|
415 |
+
|
416 |
+
template <typename T>
|
417 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLayeredLod(T *ptr, cudaTextureObject_t obj, float x, float y, int layer, float level)
|
418 |
+
{
|
419 |
+
__nv_tex_surf_handler("__itex2DLayeredLod", ptr, obj, x, y, layer, level);
|
420 |
+
}
|
421 |
+
|
422 |
+
template <class T>
|
423 |
+
static __device__ T tex2DLayeredLod(cudaTextureObject_t texObject, float x, float y, int layer, float level)
|
424 |
+
{
|
425 |
+
T ret;
|
426 |
+
tex2DLayeredLod(&ret, texObject, x, y, layer, level);
|
427 |
+
return ret;
|
428 |
+
}
|
429 |
+
|
430 |
+
#if __NV_TEX_SPARSE
|
431 |
+
template <typename T>
|
432 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLayeredLod(T *ptr, cudaTextureObject_t obj, float x, float y, int layer, float level, bool* isResident)
|
433 |
+
{
|
434 |
+
unsigned char res;
|
435 |
+
__nv_tex_surf_handler("__itex2DLayeredLod_sparse", ptr, obj, x, y, layer, level, &res);
|
436 |
+
*isResident = (res != 0);
|
437 |
+
}
|
438 |
+
|
439 |
+
template <class T>
|
440 |
+
static __device__ T tex2DLayeredLod(cudaTextureObject_t texObject, float x, float y, int layer, float level, bool* isResident)
|
441 |
+
{
|
442 |
+
T ret;
|
443 |
+
tex2DLayeredLod(&ret, texObject, x, y, layer, level, isResident);
|
444 |
+
return ret;
|
445 |
+
}
|
446 |
+
#endif /* __NV_TEX_SPARSE */
|
447 |
+
|
448 |
+
template <typename T>
|
449 |
+
static __device__ typename __nv_itex_trait<T>::type texCubemapLod(T *ptr, cudaTextureObject_t obj, float x, float y, float z, float level)
|
450 |
+
{
|
451 |
+
__nv_tex_surf_handler("__itexCubemapLod", ptr, obj, x, y, z, level);
|
452 |
+
}
|
453 |
+
|
454 |
+
template <class T>
|
455 |
+
static __device__ T texCubemapLod(cudaTextureObject_t texObject, float x, float y, float z, float level)
|
456 |
+
{
|
457 |
+
T ret;
|
458 |
+
texCubemapLod(&ret, texObject, x, y, z, level);
|
459 |
+
return ret;
|
460 |
+
}
|
461 |
+
|
462 |
+
|
463 |
+
template <typename T>
|
464 |
+
static __device__ typename __nv_itex_trait<T>::type texCubemapGrad(T *ptr, cudaTextureObject_t obj, float x, float y, float z, float4 dPdx, float4 dPdy)
|
465 |
+
{
|
466 |
+
__nv_tex_surf_handler("__itexCubemapGrad_v2", ptr, obj, x, y, z, &dPdx, &dPdy);
|
467 |
+
}
|
468 |
+
|
469 |
+
template <class T>
|
470 |
+
static __device__ T texCubemapGrad(cudaTextureObject_t texObject, float x, float y, float z, float4 dPdx, float4 dPdy)
|
471 |
+
{
|
472 |
+
T ret;
|
473 |
+
texCubemapGrad(&ret, texObject, x, y, z, dPdx, dPdy);
|
474 |
+
return ret;
|
475 |
+
}
|
476 |
+
|
477 |
+
template <typename T>
|
478 |
+
static __device__ typename __nv_itex_trait<T>::type texCubemapLayeredLod(T *ptr, cudaTextureObject_t obj, float x, float y, float z, int layer, float level)
|
479 |
+
{
|
480 |
+
__nv_tex_surf_handler("__itexCubemapLayeredLod", ptr, obj, x, y, z, layer, level);
|
481 |
+
}
|
482 |
+
|
483 |
+
template <class T>
|
484 |
+
static __device__ T texCubemapLayeredLod(cudaTextureObject_t texObject, float x, float y, float z, int layer, float level)
|
485 |
+
{
|
486 |
+
T ret;
|
487 |
+
texCubemapLayeredLod(&ret, texObject, x, y, z, layer, level);
|
488 |
+
return ret;
|
489 |
+
}
|
490 |
+
|
491 |
+
template <typename T>
|
492 |
+
static __device__ typename __nv_itex_trait<T>::type tex1DGrad(T *ptr, cudaTextureObject_t obj, float x, float dPdx, float dPdy)
|
493 |
+
{
|
494 |
+
__nv_tex_surf_handler("__itex1DGrad", ptr, obj, x, dPdx, dPdy);
|
495 |
+
}
|
496 |
+
|
497 |
+
template <class T>
|
498 |
+
static __device__ T tex1DGrad(cudaTextureObject_t texObject, float x, float dPdx, float dPdy)
|
499 |
+
{
|
500 |
+
T ret;
|
501 |
+
tex1DGrad(&ret, texObject, x, dPdx, dPdy);
|
502 |
+
return ret;
|
503 |
+
}
|
504 |
+
|
505 |
+
|
506 |
+
template <typename T>
|
507 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DGrad(T *ptr, cudaTextureObject_t obj, float x, float y, float2 dPdx, float2 dPdy)
|
508 |
+
{
|
509 |
+
__nv_tex_surf_handler("__itex2DGrad_v2", ptr, obj, x, y, &dPdx, &dPdy);
|
510 |
+
}
|
511 |
+
|
512 |
+
template <class T>
|
513 |
+
static __device__ T tex2DGrad(cudaTextureObject_t texObject, float x, float y, float2 dPdx, float2 dPdy)
|
514 |
+
{
|
515 |
+
T ret;
|
516 |
+
tex2DGrad(&ret, texObject, x, y, dPdx, dPdy);
|
517 |
+
return ret;
|
518 |
+
}
|
519 |
+
|
520 |
+
#if __NV_TEX_SPARSE
|
521 |
+
template <typename T>
|
522 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DGrad(T *ptr, cudaTextureObject_t obj, float x, float y, float2 dPdx, float2 dPdy, bool* isResident)
|
523 |
+
{
|
524 |
+
unsigned char res;
|
525 |
+
__nv_tex_surf_handler("__itex2DGrad_sparse", ptr, obj, x, y, &dPdx, &dPdy, &res);
|
526 |
+
*isResident = (res != 0);
|
527 |
+
}
|
528 |
+
|
529 |
+
template <class T>
|
530 |
+
static __device__ T tex2DGrad(cudaTextureObject_t texObject, float x, float y, float2 dPdx, float2 dPdy, bool* isResident)
|
531 |
+
{
|
532 |
+
T ret;
|
533 |
+
tex2DGrad(&ret, texObject, x, y, dPdx, dPdy, isResident);
|
534 |
+
return ret;
|
535 |
+
}
|
536 |
+
#endif /* __NV_TEX_SPARSE */
|
537 |
+
|
538 |
+
|
539 |
+
template <typename T>
|
540 |
+
static __device__ typename __nv_itex_trait<T>::type tex3DGrad(T *ptr, cudaTextureObject_t obj, float x, float y, float z, float4 dPdx, float4 dPdy)
|
541 |
+
{
|
542 |
+
__nv_tex_surf_handler("__itex3DGrad_v2", ptr, obj, x, y, z, &dPdx, &dPdy);
|
543 |
+
}
|
544 |
+
|
545 |
+
template <class T>
|
546 |
+
static __device__ T tex3DGrad(cudaTextureObject_t texObject, float x, float y, float z, float4 dPdx, float4 dPdy)
|
547 |
+
{
|
548 |
+
T ret;
|
549 |
+
tex3DGrad(&ret, texObject, x, y, z, dPdx, dPdy);
|
550 |
+
return ret;
|
551 |
+
}
|
552 |
+
|
553 |
+
#if __NV_TEX_SPARSE
|
554 |
+
template <typename T>
|
555 |
+
static __device__ typename __nv_itex_trait<T>::type tex3DGrad(T *ptr, cudaTextureObject_t obj, float x, float y, float z, float4 dPdx, float4 dPdy, bool* isResident)
|
556 |
+
{
|
557 |
+
unsigned char res;
|
558 |
+
__nv_tex_surf_handler("__itex3DGrad_sparse", ptr, obj, x, y, z, &dPdx, &dPdy, &res);
|
559 |
+
*isResident = (res != 0);
|
560 |
+
}
|
561 |
+
|
562 |
+
template <class T>
|
563 |
+
static __device__ T tex3DGrad(cudaTextureObject_t texObject, float x, float y, float z, float4 dPdx, float4 dPdy, bool* isResident)
|
564 |
+
{
|
565 |
+
T ret;
|
566 |
+
tex3DGrad(&ret, texObject, x, y, z, dPdx, dPdy, isResident);
|
567 |
+
return ret;
|
568 |
+
}
|
569 |
+
|
570 |
+
#endif /* __NV_TEX_SPARSE */
|
571 |
+
|
572 |
+
|
573 |
+
template <typename T>
|
574 |
+
static __device__ typename __nv_itex_trait<T>::type tex1DLayeredGrad(T *ptr, cudaTextureObject_t obj, float x, int layer, float dPdx, float dPdy)
|
575 |
+
{
|
576 |
+
__nv_tex_surf_handler("__itex1DLayeredGrad", ptr, obj, x, layer, dPdx, dPdy);
|
577 |
+
}
|
578 |
+
|
579 |
+
template <class T>
|
580 |
+
static __device__ T tex1DLayeredGrad(cudaTextureObject_t texObject, float x, int layer, float dPdx, float dPdy)
|
581 |
+
{
|
582 |
+
T ret;
|
583 |
+
tex1DLayeredGrad(&ret, texObject, x, layer, dPdx, dPdy);
|
584 |
+
return ret;
|
585 |
+
}
|
586 |
+
|
587 |
+
|
588 |
+
template <typename T>
|
589 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLayeredGrad(T * ptr, cudaTextureObject_t obj, float x, float y, int layer, float2 dPdx, float2 dPdy)
|
590 |
+
{
|
591 |
+
__nv_tex_surf_handler("__itex2DLayeredGrad_v2", ptr, obj, x, y, layer, &dPdx, &dPdy);
|
592 |
+
}
|
593 |
+
|
594 |
+
template <class T>
|
595 |
+
static __device__ T tex2DLayeredGrad(cudaTextureObject_t texObject, float x, float y, int layer, float2 dPdx, float2 dPdy)
|
596 |
+
{
|
597 |
+
T ret;
|
598 |
+
tex2DLayeredGrad(&ret, texObject, x, y, layer, dPdx, dPdy);
|
599 |
+
return ret;
|
600 |
+
}
|
601 |
+
|
602 |
+
#if __NV_TEX_SPARSE
|
603 |
+
template <typename T>
|
604 |
+
static __device__ typename __nv_itex_trait<T>::type tex2DLayeredGrad(T * ptr, cudaTextureObject_t obj, float x, float y, int layer, float2 dPdx, float2 dPdy, bool* isResident)
|
605 |
+
{
|
606 |
+
unsigned char res;
|
607 |
+
__nv_tex_surf_handler("__itex2DLayeredGrad_sparse", ptr, obj, x, y, layer, &dPdx, &dPdy, &res);
|
608 |
+
*isResident = (res != 0);
|
609 |
+
}
|
610 |
+
|
611 |
+
template <class T>
|
612 |
+
static __device__ T tex2DLayeredGrad(cudaTextureObject_t texObject, float x, float y, int layer, float2 dPdx, float2 dPdy, bool* isResident)
|
613 |
+
{
|
614 |
+
T ret;
|
615 |
+
tex2DLayeredGrad(&ret, texObject, x, y, layer, dPdx, dPdy, isResident);
|
616 |
+
return ret;
|
617 |
+
}
|
618 |
+
#endif /* __NV_TEX_SPARSE */
|
619 |
+
|
620 |
+
|
621 |
+
template <typename T>
|
622 |
+
static __device__ typename __nv_itex_trait<T>::type texCubemapLayeredGrad(T *ptr, cudaTextureObject_t obj, float x, float y, float z, int layer, float4 dPdx, float4 dPdy)
|
623 |
+
{
|
624 |
+
__nv_tex_surf_handler("__itexCubemapLayeredGrad_v2", ptr, obj, x, y, z, layer, &dPdx, &dPdy);
|
625 |
+
}
|
626 |
+
|
627 |
+
template <class T>
|
628 |
+
static __device__ T texCubemapLayeredGrad(cudaTextureObject_t texObject, float x, float y, float z, int layer, float4 dPdx, float4 dPdy)
|
629 |
+
{
|
630 |
+
T ret;
|
631 |
+
texCubemapLayeredGrad(&ret, texObject, x, y, z, layer, dPdx, dPdy);
|
632 |
+
return ret;
|
633 |
+
}
|
634 |
+
|
635 |
+
#undef __NV_TEX_SPARSE
|
636 |
+
|
637 |
+
#endif // __cplusplus && __CUDACC__
|
638 |
+
#endif // __TEXTURE_INDIRECT_FUNCTIONS_H__
|
env-llmeval/lib/python3.10/site-packages/nvidia/cuda_runtime/include/texture_types.h
ADDED
@@ -0,0 +1,177 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 1993-2012 NVIDIA Corporation. All rights reserved.
|
3 |
+
*
|
4 |
+
* NOTICE TO LICENSEE:
|
5 |
+
*
|
6 |
+
* This source code and/or documentation ("Licensed Deliverables") are
|
7 |
+
* subject to NVIDIA intellectual property rights under U.S. and
|
8 |
+
* international Copyright laws.
|
9 |
+
*
|
10 |
+
* These Licensed Deliverables contained herein is PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
|
12 |
+
* conditions of a form of NVIDIA software license agreement by and
|
13 |
+
* between NVIDIA and Licensee ("License Agreement") or electronically
|
14 |
+
* accepted by Licensee. Notwithstanding any terms or conditions to
|
15 |
+
* the contrary in the License Agreement, reproduction or disclosure
|
16 |
+
* of the Licensed Deliverables to any third party without the express
|
17 |
+
* written consent of NVIDIA is prohibited.
|
18 |
+
*
|
19 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
20 |
+
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
|
21 |
+
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
|
22 |
+
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
|
23 |
+
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
|
24 |
+
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
|
25 |
+
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
|
26 |
+
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
|
27 |
+
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
|
28 |
+
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
|
29 |
+
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
|
30 |
+
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
|
31 |
+
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
|
32 |
+
* OF THESE LICENSED DELIVERABLES.
|
33 |
+
*
|
34 |
+
* U.S. Government End Users. These Licensed Deliverables are a
|
35 |
+
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
|
36 |
+
* 1995), consisting of "commercial computer software" and "commercial
|
37 |
+
* computer software documentation" as such terms are used in 48
|
38 |
+
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
|
39 |
+
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
|
40 |
+
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
|
41 |
+
* U.S. Government End Users acquire the Licensed Deliverables with
|
42 |
+
* only those rights set forth herein.
|
43 |
+
*
|
44 |
+
* Any use of the Licensed Deliverables in individual and commercial
|
45 |
+
* software must include, in the user documentation and internal
|
46 |
+
* comments to the code, the above Disclaimer and U.S. Government End
|
47 |
+
* Users Notice.
|
48 |
+
*/
|
49 |
+
|
50 |
+
#if !defined(__TEXTURE_TYPES_H__)
|
51 |
+
#define __TEXTURE_TYPES_H__
|
52 |
+
|
53 |
+
/*******************************************************************************
|
54 |
+
* *
|
55 |
+
* *
|
56 |
+
* *
|
57 |
+
*******************************************************************************/
|
58 |
+
|
59 |
+
#include "driver_types.h"
|
60 |
+
|
61 |
+
/**
|
62 |
+
* \addtogroup CUDART_TYPES
|
63 |
+
*
|
64 |
+
* @{
|
65 |
+
*/
|
66 |
+
|
67 |
+
/*******************************************************************************
|
68 |
+
* *
|
69 |
+
* *
|
70 |
+
* *
|
71 |
+
*******************************************************************************/
|
72 |
+
|
73 |
+
#define cudaTextureType1D 0x01
|
74 |
+
#define cudaTextureType2D 0x02
|
75 |
+
#define cudaTextureType3D 0x03
|
76 |
+
#define cudaTextureTypeCubemap 0x0C
|
77 |
+
#define cudaTextureType1DLayered 0xF1
|
78 |
+
#define cudaTextureType2DLayered 0xF2
|
79 |
+
#define cudaTextureTypeCubemapLayered 0xFC
|
80 |
+
|
81 |
+
/**
|
82 |
+
* CUDA texture address modes
|
83 |
+
*/
|
84 |
+
enum __device_builtin__ cudaTextureAddressMode
|
85 |
+
{
|
86 |
+
cudaAddressModeWrap = 0, /**< Wrapping address mode */
|
87 |
+
cudaAddressModeClamp = 1, /**< Clamp to edge address mode */
|
88 |
+
cudaAddressModeMirror = 2, /**< Mirror address mode */
|
89 |
+
cudaAddressModeBorder = 3 /**< Border address mode */
|
90 |
+
};
|
91 |
+
|
92 |
+
/**
|
93 |
+
* CUDA texture filter modes
|
94 |
+
*/
|
95 |
+
enum __device_builtin__ cudaTextureFilterMode
|
96 |
+
{
|
97 |
+
cudaFilterModePoint = 0, /**< Point filter mode */
|
98 |
+
cudaFilterModeLinear = 1 /**< Linear filter mode */
|
99 |
+
};
|
100 |
+
|
101 |
+
/**
|
102 |
+
* CUDA texture read modes
|
103 |
+
*/
|
104 |
+
enum __device_builtin__ cudaTextureReadMode
|
105 |
+
{
|
106 |
+
cudaReadModeElementType = 0, /**< Read texture as specified element type */
|
107 |
+
cudaReadModeNormalizedFloat = 1 /**< Read texture as normalized float */
|
108 |
+
};
|
109 |
+
|
110 |
+
/**
|
111 |
+
* CUDA texture descriptor
|
112 |
+
*/
|
113 |
+
struct __device_builtin__ cudaTextureDesc
|
114 |
+
{
|
115 |
+
/**
|
116 |
+
* Texture address mode for up to 3 dimensions
|
117 |
+
*/
|
118 |
+
enum cudaTextureAddressMode addressMode[3];
|
119 |
+
/**
|
120 |
+
* Texture filter mode
|
121 |
+
*/
|
122 |
+
enum cudaTextureFilterMode filterMode;
|
123 |
+
/**
|
124 |
+
* Texture read mode
|
125 |
+
*/
|
126 |
+
enum cudaTextureReadMode readMode;
|
127 |
+
/**
|
128 |
+
* Perform sRGB->linear conversion during texture read
|
129 |
+
*/
|
130 |
+
int sRGB;
|
131 |
+
/**
|
132 |
+
* Texture Border Color
|
133 |
+
*/
|
134 |
+
float borderColor[4];
|
135 |
+
/**
|
136 |
+
* Indicates whether texture reads are normalized or not
|
137 |
+
*/
|
138 |
+
int normalizedCoords;
|
139 |
+
/**
|
140 |
+
* Limit to the anisotropy ratio
|
141 |
+
*/
|
142 |
+
unsigned int maxAnisotropy;
|
143 |
+
/**
|
144 |
+
* Mipmap filter mode
|
145 |
+
*/
|
146 |
+
enum cudaTextureFilterMode mipmapFilterMode;
|
147 |
+
/**
|
148 |
+
* Offset applied to the supplied mipmap level
|
149 |
+
*/
|
150 |
+
float mipmapLevelBias;
|
151 |
+
/**
|
152 |
+
* Lower end of the mipmap level range to clamp access to
|
153 |
+
*/
|
154 |
+
float minMipmapLevelClamp;
|
155 |
+
/**
|
156 |
+
* Upper end of the mipmap level range to clamp access to
|
157 |
+
*/
|
158 |
+
float maxMipmapLevelClamp;
|
159 |
+
/**
|
160 |
+
* Disable any trilinear filtering optimizations.
|
161 |
+
*/
|
162 |
+
int disableTrilinearOptimization;
|
163 |
+
/**
|
164 |
+
* Enable seamless cube map filtering.
|
165 |
+
*/
|
166 |
+
int seamlessCubemap;
|
167 |
+
};
|
168 |
+
|
169 |
+
/**
|
170 |
+
* An opaque value that represents a CUDA texture object
|
171 |
+
*/
|
172 |
+
typedef __device_builtin__ unsigned long long cudaTextureObject_t;
|
173 |
+
|
174 |
+
/** @} */
|
175 |
+
/** @} */ /* END CUDART_TYPES */
|
176 |
+
|
177 |
+
#endif /* !__TEXTURE_TYPES_H__ */
|