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- .gitattributes +4 -0
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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 CUBLAS library, defining the API
|
52 |
+
*
|
53 |
+
* CUBLAS is an implementation of BLAS (Basic Linear Algebra Subroutines)
|
54 |
+
* on top of the CUDA runtime.
|
55 |
+
*/
|
56 |
+
|
57 |
+
#if !defined(CUBLAS_H_)
|
58 |
+
#define CUBLAS_H_
|
59 |
+
|
60 |
+
#if defined(CUBLAS_V2_H_)
|
61 |
+
#error "It is an error to include both cublas.h and cublas_v2.h"
|
62 |
+
#endif
|
63 |
+
|
64 |
+
#include <cuda_runtime.h>
|
65 |
+
|
66 |
+
#ifndef CUBLASWINAPI
|
67 |
+
#ifdef _WIN32
|
68 |
+
#define CUBLASWINAPI __stdcall
|
69 |
+
#else
|
70 |
+
#define CUBLASWINAPI
|
71 |
+
#endif
|
72 |
+
#endif
|
73 |
+
|
74 |
+
#undef CUBLASAPI
|
75 |
+
#ifdef __CUDACC__
|
76 |
+
#define CUBLASAPI __host__
|
77 |
+
#else
|
78 |
+
#define CUBLASAPI
|
79 |
+
#endif
|
80 |
+
|
81 |
+
#include "cublas_api.h"
|
82 |
+
|
83 |
+
#if defined(__cplusplus)
|
84 |
+
extern "C" {
|
85 |
+
#endif
|
86 |
+
|
87 |
+
/* CUBLAS data types */
|
88 |
+
#define cublasStatus cublasStatus_t
|
89 |
+
|
90 |
+
cublasStatus CUBLASWINAPI cublasInit(void);
|
91 |
+
cublasStatus CUBLASWINAPI cublasShutdown(void);
|
92 |
+
cublasStatus CUBLASWINAPI cublasGetError(void);
|
93 |
+
|
94 |
+
cublasStatus CUBLASWINAPI cublasGetVersion(int* version);
|
95 |
+
cublasStatus CUBLASWINAPI cublasAlloc(int n, int elemSize, void** devicePtr);
|
96 |
+
|
97 |
+
cublasStatus CUBLASWINAPI cublasFree(void* devicePtr);
|
98 |
+
|
99 |
+
cublasStatus CUBLASWINAPI cublasSetKernelStream(cudaStream_t stream);
|
100 |
+
|
101 |
+
/* ---------------- CUBLAS BLAS1 functions ---------------- */
|
102 |
+
/* NRM2 */
|
103 |
+
float CUBLASWINAPI cublasSnrm2(int n, const float* x, int incx);
|
104 |
+
double CUBLASWINAPI cublasDnrm2(int n, const double* x, int incx);
|
105 |
+
float CUBLASWINAPI cublasScnrm2(int n, const cuComplex* x, int incx);
|
106 |
+
double CUBLASWINAPI cublasDznrm2(int n, const cuDoubleComplex* x, int incx);
|
107 |
+
/*------------------------------------------------------------------------*/
|
108 |
+
/* DOT */
|
109 |
+
float CUBLASWINAPI cublasSdot(int n, const float* x, int incx, const float* y, int incy);
|
110 |
+
double CUBLASWINAPI cublasDdot(int n, const double* x, int incx, const double* y, int incy);
|
111 |
+
cuComplex CUBLASWINAPI cublasCdotu(int n, const cuComplex* x, int incx, const cuComplex* y, int incy);
|
112 |
+
cuComplex CUBLASWINAPI cublasCdotc(int n, const cuComplex* x, int incx, const cuComplex* y, int incy);
|
113 |
+
cuDoubleComplex CUBLASWINAPI cublasZdotu(int n, const cuDoubleComplex* x, int incx, const cuDoubleComplex* y, int incy);
|
114 |
+
cuDoubleComplex CUBLASWINAPI cublasZdotc(int n, const cuDoubleComplex* x, int incx, const cuDoubleComplex* y, int incy);
|
115 |
+
/*------------------------------------------------------------------------*/
|
116 |
+
/* SCAL */
|
117 |
+
void CUBLASWINAPI cublasSscal(int n, float alpha, float* x, int incx);
|
118 |
+
void CUBLASWINAPI cublasDscal(int n, double alpha, double* x, int incx);
|
119 |
+
void CUBLASWINAPI cublasCscal(int n, cuComplex alpha, cuComplex* x, int incx);
|
120 |
+
void CUBLASWINAPI cublasZscal(int n, cuDoubleComplex alpha, cuDoubleComplex* x, int incx);
|
121 |
+
|
122 |
+
void CUBLASWINAPI cublasCsscal(int n, float alpha, cuComplex* x, int incx);
|
123 |
+
void CUBLASWINAPI cublasZdscal(int n, double alpha, cuDoubleComplex* x, int incx);
|
124 |
+
/*------------------------------------------------------------------------*/
|
125 |
+
/* AXPY */
|
126 |
+
void CUBLASWINAPI cublasSaxpy(int n, float alpha, const float* x, int incx, float* y, int incy);
|
127 |
+
void CUBLASWINAPI cublasDaxpy(int n, double alpha, const double* x, int incx, double* y, int incy);
|
128 |
+
void CUBLASWINAPI cublasCaxpy(int n, cuComplex alpha, const cuComplex* x, int incx, cuComplex* y, int incy);
|
129 |
+
void CUBLASWINAPI
|
130 |
+
cublasZaxpy(int n, cuDoubleComplex alpha, const cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy);
|
131 |
+
/*------------------------------------------------------------------------*/
|
132 |
+
/* COPY */
|
133 |
+
void CUBLASWINAPI cublasScopy(int n, const float* x, int incx, float* y, int incy);
|
134 |
+
void CUBLASWINAPI cublasDcopy(int n, const double* x, int incx, double* y, int incy);
|
135 |
+
void CUBLASWINAPI cublasCcopy(int n, const cuComplex* x, int incx, cuComplex* y, int incy);
|
136 |
+
void CUBLASWINAPI cublasZcopy(int n, const cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy);
|
137 |
+
/*------------------------------------------------------------------------*/
|
138 |
+
/* SWAP */
|
139 |
+
void CUBLASWINAPI cublasSswap(int n, float* x, int incx, float* y, int incy);
|
140 |
+
void CUBLASWINAPI cublasDswap(int n, double* x, int incx, double* y, int incy);
|
141 |
+
void CUBLASWINAPI cublasCswap(int n, cuComplex* x, int incx, cuComplex* y, int incy);
|
142 |
+
void CUBLASWINAPI cublasZswap(int n, cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy);
|
143 |
+
/*------------------------------------------------------------------------*/
|
144 |
+
/* AMAX */
|
145 |
+
int CUBLASWINAPI cublasIsamax(int n, const float* x, int incx);
|
146 |
+
int CUBLASWINAPI cublasIdamax(int n, const double* x, int incx);
|
147 |
+
int CUBLASWINAPI cublasIcamax(int n, const cuComplex* x, int incx);
|
148 |
+
int CUBLASWINAPI cublasIzamax(int n, const cuDoubleComplex* x, int incx);
|
149 |
+
/*------------------------------------------------------------------------*/
|
150 |
+
/* AMIN */
|
151 |
+
int CUBLASWINAPI cublasIsamin(int n, const float* x, int incx);
|
152 |
+
int CUBLASWINAPI cublasIdamin(int n, const double* x, int incx);
|
153 |
+
|
154 |
+
int CUBLASWINAPI cublasIcamin(int n, const cuComplex* x, int incx);
|
155 |
+
int CUBLASWINAPI cublasIzamin(int n, const cuDoubleComplex* x, int incx);
|
156 |
+
/*------------------------------------------------------------------------*/
|
157 |
+
/* ASUM */
|
158 |
+
float CUBLASWINAPI cublasSasum(int n, const float* x, int incx);
|
159 |
+
double CUBLASWINAPI cublasDasum(int n, const double* x, int incx);
|
160 |
+
float CUBLASWINAPI cublasScasum(int n, const cuComplex* x, int incx);
|
161 |
+
double CUBLASWINAPI cublasDzasum(int n, const cuDoubleComplex* x, int incx);
|
162 |
+
/*------------------------------------------------------------------------*/
|
163 |
+
/* ROT */
|
164 |
+
void CUBLASWINAPI cublasSrot(int n, float* x, int incx, float* y, int incy, float sc, float ss);
|
165 |
+
void CUBLASWINAPI cublasDrot(int n, double* x, int incx, double* y, int incy, double sc, double ss);
|
166 |
+
void CUBLASWINAPI cublasCrot(int n, cuComplex* x, int incx, cuComplex* y, int incy, float c, cuComplex s);
|
167 |
+
void CUBLASWINAPI
|
168 |
+
cublasZrot(int n, cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy, double sc, cuDoubleComplex cs);
|
169 |
+
void CUBLASWINAPI cublasCsrot(int n, cuComplex* x, int incx, cuComplex* y, int incy, float c, float s);
|
170 |
+
void CUBLASWINAPI cublasZdrot(int n, cuDoubleComplex* x, int incx, cuDoubleComplex* y, int incy, double c, double s);
|
171 |
+
/*------------------------------------------------------------------------*/
|
172 |
+
/* ROTG */
|
173 |
+
void CUBLASWINAPI cublasSrotg(float* sa, float* sb, float* sc, float* ss);
|
174 |
+
void CUBLASWINAPI cublasDrotg(double* sa, double* sb, double* sc, double* ss);
|
175 |
+
void CUBLASWINAPI cublasCrotg(cuComplex* ca, cuComplex cb, float* sc, cuComplex* cs);
|
176 |
+
void CUBLASWINAPI cublasZrotg(cuDoubleComplex* ca, cuDoubleComplex cb, double* sc, cuDoubleComplex* cs);
|
177 |
+
/*------------------------------------------------------------------------*/
|
178 |
+
/* ROTM */
|
179 |
+
void CUBLASWINAPI cublasSrotm(int n, float* x, int incx, float* y, int incy, const float* sparam);
|
180 |
+
void CUBLASWINAPI cublasDrotm(int n, double* x, int incx, double* y, int incy, const double* sparam);
|
181 |
+
/*------------------------------------------------------------------------*/
|
182 |
+
/* ROTMG */
|
183 |
+
void CUBLASWINAPI cublasSrotmg(float* sd1, float* sd2, float* sx1, const float* sy1, float* sparam);
|
184 |
+
void CUBLASWINAPI cublasDrotmg(double* sd1, double* sd2, double* sx1, const double* sy1, double* sparam);
|
185 |
+
|
186 |
+
/* --------------- CUBLAS BLAS2 functions ---------------- */
|
187 |
+
/* GEMV */
|
188 |
+
void CUBLASWINAPI cublasSgemv(char trans,
|
189 |
+
int m,
|
190 |
+
int n,
|
191 |
+
float alpha,
|
192 |
+
const float* A,
|
193 |
+
int lda,
|
194 |
+
const float* x,
|
195 |
+
int incx,
|
196 |
+
float beta,
|
197 |
+
float* y,
|
198 |
+
int incy);
|
199 |
+
void CUBLASWINAPI cublasDgemv(char trans,
|
200 |
+
int m,
|
201 |
+
int n,
|
202 |
+
double alpha,
|
203 |
+
const double* A,
|
204 |
+
int lda,
|
205 |
+
const double* x,
|
206 |
+
int incx,
|
207 |
+
double beta,
|
208 |
+
double* y,
|
209 |
+
int incy);
|
210 |
+
void CUBLASWINAPI cublasCgemv(char trans,
|
211 |
+
int m,
|
212 |
+
int n,
|
213 |
+
cuComplex alpha,
|
214 |
+
const cuComplex* A,
|
215 |
+
int lda,
|
216 |
+
const cuComplex* x,
|
217 |
+
int incx,
|
218 |
+
cuComplex beta,
|
219 |
+
cuComplex* y,
|
220 |
+
int incy);
|
221 |
+
void CUBLASWINAPI cublasZgemv(char trans,
|
222 |
+
int m,
|
223 |
+
int n,
|
224 |
+
cuDoubleComplex alpha,
|
225 |
+
const cuDoubleComplex* A,
|
226 |
+
int lda,
|
227 |
+
const cuDoubleComplex* x,
|
228 |
+
int incx,
|
229 |
+
cuDoubleComplex beta,
|
230 |
+
cuDoubleComplex* y,
|
231 |
+
int incy);
|
232 |
+
/*------------------------------------------------------------------------*/
|
233 |
+
/* GBMV */
|
234 |
+
void CUBLASWINAPI cublasSgbmv(char trans,
|
235 |
+
int m,
|
236 |
+
int n,
|
237 |
+
int kl,
|
238 |
+
int ku,
|
239 |
+
float alpha,
|
240 |
+
const float* A,
|
241 |
+
int lda,
|
242 |
+
const float* x,
|
243 |
+
int incx,
|
244 |
+
float beta,
|
245 |
+
float* y,
|
246 |
+
int incy);
|
247 |
+
void CUBLASWINAPI cublasDgbmv(char trans,
|
248 |
+
int m,
|
249 |
+
int n,
|
250 |
+
int kl,
|
251 |
+
int ku,
|
252 |
+
double alpha,
|
253 |
+
const double* A,
|
254 |
+
int lda,
|
255 |
+
const double* x,
|
256 |
+
int incx,
|
257 |
+
double beta,
|
258 |
+
double* y,
|
259 |
+
int incy);
|
260 |
+
void CUBLASWINAPI cublasCgbmv(char trans,
|
261 |
+
int m,
|
262 |
+
int n,
|
263 |
+
int kl,
|
264 |
+
int ku,
|
265 |
+
cuComplex alpha,
|
266 |
+
const cuComplex* A,
|
267 |
+
int lda,
|
268 |
+
const cuComplex* x,
|
269 |
+
int incx,
|
270 |
+
cuComplex beta,
|
271 |
+
cuComplex* y,
|
272 |
+
int incy);
|
273 |
+
void CUBLASWINAPI cublasZgbmv(char trans,
|
274 |
+
int m,
|
275 |
+
int n,
|
276 |
+
int kl,
|
277 |
+
int ku,
|
278 |
+
cuDoubleComplex alpha,
|
279 |
+
const cuDoubleComplex* A,
|
280 |
+
int lda,
|
281 |
+
const cuDoubleComplex* x,
|
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);
|
289 |
+
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_) */
|
llmeval-env/lib/python3.10/site-packages/nvidia/cublas/include/cublasLt.h
ADDED
@@ -0,0 +1,1815 @@
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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 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 */
|
llmeval-env/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_) */
|
llmeval-env/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
|
|
llmeval-env/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_) */
|
llmeval-env/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_) */
|
llmeval-env/lib/python3.10/site-packages/nvidia/cublas/lib/__init__.py
ADDED
File without changes
|
llmeval-env/lib/python3.10/site-packages/nvidia/cublas/lib/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (190 Bytes). View file
|
|
llmeval-env/lib/python3.10/site-packages/nvidia/cublas/lib/libnvblas.so.12
ADDED
Binary file (737 kB). View file
|
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/include/Openacc/cupti_openacc.h
ADDED
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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 2017 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 |
+
#include <cuda_stdint.h>
|
51 |
+
|
52 |
+
#if !defined(_CUPTI_OPENACC_H_)
|
53 |
+
#define _CUPTI_OPENACC_H_
|
54 |
+
|
55 |
+
#ifndef CUPTIAPI
|
56 |
+
#ifdef _WIN32
|
57 |
+
#define CUPTIAPI __stdcall
|
58 |
+
#else
|
59 |
+
#define CUPTIAPI
|
60 |
+
#endif
|
61 |
+
#endif
|
62 |
+
|
63 |
+
#if defined(__LP64__)
|
64 |
+
#define CUPTILP64 1
|
65 |
+
#elif defined(_WIN64)
|
66 |
+
#define CUPTILP64 1
|
67 |
+
#else
|
68 |
+
#undef CUPTILP64
|
69 |
+
#endif
|
70 |
+
|
71 |
+
#if defined(__cplusplus)
|
72 |
+
extern "C" {
|
73 |
+
#endif
|
74 |
+
|
75 |
+
#if defined(__GNUC__) && defined(CUPTI_LIB)
|
76 |
+
#pragma GCC visibility push(default)
|
77 |
+
#endif
|
78 |
+
|
79 |
+
/**
|
80 |
+
* \brief Initialize OpenACC support
|
81 |
+
*
|
82 |
+
* \param profRegister function of type acc_prof_reg as obtained from acc_register_library
|
83 |
+
* \param profUnregister function of type acc_prof_reg as obtained from acc_register_library
|
84 |
+
* \param profLookup function of type acc_prof_lookup as obtained from acc_register_library
|
85 |
+
*/
|
86 |
+
CUptiResult CUPTIAPI
|
87 |
+
cuptiOpenACCInitialize(void *profRegister, void *profUnregister, void *profLookup);
|
88 |
+
|
89 |
+
#if defined(__GNUC__) && defined(CUPTI_LIB)
|
90 |
+
#pragma GCC visibility pop
|
91 |
+
#endif
|
92 |
+
|
93 |
+
#if defined(__cplusplus)
|
94 |
+
}
|
95 |
+
#endif
|
96 |
+
|
97 |
+
#endif /*_CUPTI_OPENACC_H_*/
|
98 |
+
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/include/Openmp/cupti_openmp.h
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/*
|
2 |
+
* Copyright 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 |
+
#include <cuda_stdint.h>
|
51 |
+
#include "Openmp/omp-tools.h"
|
52 |
+
|
53 |
+
#if !defined(_CUPTI_OPENMP_H_)
|
54 |
+
#define _CUPTI_OPENMP_H_
|
55 |
+
|
56 |
+
#ifndef CUPTIAPI
|
57 |
+
#ifdef _WIN32
|
58 |
+
#define CUPTIAPI __stdcall
|
59 |
+
#else
|
60 |
+
#define CUPTIAPI
|
61 |
+
#endif
|
62 |
+
#endif
|
63 |
+
|
64 |
+
#if defined(__LP64__)
|
65 |
+
#define CUPTILP64 1
|
66 |
+
#elif defined(_WIN64)
|
67 |
+
#define CUPTILP64 1
|
68 |
+
#else
|
69 |
+
#undef CUPTILP64
|
70 |
+
#endif
|
71 |
+
|
72 |
+
#if defined(__cplusplus)
|
73 |
+
extern "C" {
|
74 |
+
#endif
|
75 |
+
|
76 |
+
#if defined(__GNUC__) && defined(CUPTI_LIB)
|
77 |
+
#pragma GCC visibility push(default)
|
78 |
+
#endif
|
79 |
+
|
80 |
+
/**
|
81 |
+
* \brief Initialize OPENMP support (deprecated, used before OpenMP 5.0)
|
82 |
+
*
|
83 |
+
*/
|
84 |
+
int CUPTIAPI cuptiOpenMpInitialize(ompt_function_lookup_t ompt_fn_lookup, const char *runtime_version, unsigned int ompt_version);
|
85 |
+
|
86 |
+
/**
|
87 |
+
* \brief Initialize OPENMP support
|
88 |
+
*
|
89 |
+
*/
|
90 |
+
int CUPTIAPI cuptiOpenMpInitialize_v2(ompt_function_lookup_t lookup, int initial_device_num, ompt_data_t *tool_data);
|
91 |
+
|
92 |
+
#if defined(__GNUC__) && defined(CUPTI_LIB)
|
93 |
+
#pragma GCC visibility pop
|
94 |
+
#endif
|
95 |
+
|
96 |
+
#if defined(__cplusplus)
|
97 |
+
}
|
98 |
+
#endif
|
99 |
+
|
100 |
+
#endif /*_CUPTI_OPENMP_H_*/
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/include/Openmp/omp-tools.h
ADDED
@@ -0,0 +1,1083 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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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|
|
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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 |
+
* include/50/omp-tools.h.var
|
3 |
+
*/
|
4 |
+
|
5 |
+
//===----------------------------------------------------------------------===//
|
6 |
+
//
|
7 |
+
// The LLVM Compiler Infrastructure
|
8 |
+
//
|
9 |
+
// This file is dual licensed under the MIT and the University of Illinois Open
|
10 |
+
// Source Licenses. See LICENSE.txt for details.
|
11 |
+
//
|
12 |
+
//===----------------------------------------------------------------------===//
|
13 |
+
|
14 |
+
#ifndef __OMPT__
|
15 |
+
#define __OMPT__
|
16 |
+
|
17 |
+
/*****************************************************************************
|
18 |
+
* system include files
|
19 |
+
*****************************************************************************/
|
20 |
+
|
21 |
+
#include <stdint.h>
|
22 |
+
#include <stddef.h>
|
23 |
+
|
24 |
+
/*****************************************************************************
|
25 |
+
* iteration macros
|
26 |
+
*****************************************************************************/
|
27 |
+
|
28 |
+
#define FOREACH_OMPT_INQUIRY_FN(macro) \
|
29 |
+
macro (ompt_enumerate_states) \
|
30 |
+
macro (ompt_enumerate_mutex_impls) \
|
31 |
+
\
|
32 |
+
macro (ompt_set_callback) \
|
33 |
+
macro (ompt_get_callback) \
|
34 |
+
\
|
35 |
+
macro (ompt_get_state) \
|
36 |
+
\
|
37 |
+
macro (ompt_get_parallel_info) \
|
38 |
+
macro (ompt_get_task_info) \
|
39 |
+
macro (ompt_get_task_memory) \
|
40 |
+
macro (ompt_get_thread_data) \
|
41 |
+
macro (ompt_get_unique_id) \
|
42 |
+
macro (ompt_finalize_tool) \
|
43 |
+
\
|
44 |
+
macro(ompt_get_num_procs) \
|
45 |
+
macro(ompt_get_num_places) \
|
46 |
+
macro(ompt_get_place_proc_ids) \
|
47 |
+
macro(ompt_get_place_num) \
|
48 |
+
macro(ompt_get_partition_place_nums) \
|
49 |
+
macro(ompt_get_proc_id) \
|
50 |
+
\
|
51 |
+
macro(ompt_get_target_info) \
|
52 |
+
macro(ompt_get_num_devices)
|
53 |
+
|
54 |
+
#define FOREACH_OMPT_STATE(macro) \
|
55 |
+
\
|
56 |
+
/* first available state */ \
|
57 |
+
macro (ompt_state_undefined, 0x102) /* undefined thread state */ \
|
58 |
+
\
|
59 |
+
/* work states (0..15) */ \
|
60 |
+
macro (ompt_state_work_serial, 0x000) /* working outside parallel */ \
|
61 |
+
macro (ompt_state_work_parallel, 0x001) /* working within parallel */ \
|
62 |
+
macro (ompt_state_work_reduction, 0x002) /* performing a reduction */ \
|
63 |
+
\
|
64 |
+
/* barrier wait states (16..31) */ \
|
65 |
+
macro (ompt_state_wait_barrier, 0x010) /* waiting at a barrier */ \
|
66 |
+
macro (ompt_state_wait_barrier_implicit_parallel, 0x011) \
|
67 |
+
/* implicit barrier at the end of parallel region */\
|
68 |
+
macro (ompt_state_wait_barrier_implicit_workshare, 0x012) \
|
69 |
+
/* implicit barrier at the end of worksharing */ \
|
70 |
+
macro (ompt_state_wait_barrier_implicit, 0x013) /* implicit barrier */ \
|
71 |
+
macro (ompt_state_wait_barrier_explicit, 0x014) /* explicit barrier */ \
|
72 |
+
\
|
73 |
+
/* task wait states (32..63) */ \
|
74 |
+
macro (ompt_state_wait_taskwait, 0x020) /* waiting at a taskwait */ \
|
75 |
+
macro (ompt_state_wait_taskgroup, 0x021) /* waiting at a taskgroup */ \
|
76 |
+
\
|
77 |
+
/* mutex wait states (64..127) */ \
|
78 |
+
macro (ompt_state_wait_mutex, 0x040) \
|
79 |
+
macro (ompt_state_wait_lock, 0x041) /* waiting for lock */ \
|
80 |
+
macro (ompt_state_wait_critical, 0x042) /* waiting for critical */ \
|
81 |
+
macro (ompt_state_wait_atomic, 0x043) /* waiting for atomic */ \
|
82 |
+
macro (ompt_state_wait_ordered, 0x044) /* waiting for ordered */ \
|
83 |
+
\
|
84 |
+
/* target wait states (128..255) */ \
|
85 |
+
macro (ompt_state_wait_target, 0x080) /* waiting for target region */ \
|
86 |
+
macro (ompt_state_wait_target_map, 0x081) /* waiting for target data mapping operation */ \
|
87 |
+
macro (ompt_state_wait_target_update, 0x082) /* waiting for target update operation */ \
|
88 |
+
\
|
89 |
+
/* misc (256..511) */ \
|
90 |
+
macro (ompt_state_idle, 0x100) /* waiting for work */ \
|
91 |
+
macro (ompt_state_overhead, 0x101) /* overhead excluding wait states */ \
|
92 |
+
\
|
93 |
+
/* implementation-specific states (512..) */
|
94 |
+
|
95 |
+
|
96 |
+
#define FOREACH_KMP_MUTEX_IMPL(macro) \
|
97 |
+
macro (kmp_mutex_impl_none, 0) /* unknown implementation */ \
|
98 |
+
macro (kmp_mutex_impl_spin, 1) /* based on spin */ \
|
99 |
+
macro (kmp_mutex_impl_queuing, 2) /* based on some fair policy */ \
|
100 |
+
macro (kmp_mutex_impl_speculative, 3) /* based on HW-supported speculation */
|
101 |
+
|
102 |
+
#define FOREACH_OMPT_EVENT(macro) \
|
103 |
+
\
|
104 |
+
/*--- Mandatory Events ---*/ \
|
105 |
+
macro (ompt_callback_thread_begin, ompt_callback_thread_begin_t, 1) /* thread begin */ \
|
106 |
+
macro (ompt_callback_thread_end, ompt_callback_thread_end_t, 2) /* thread end */ \
|
107 |
+
\
|
108 |
+
macro (ompt_callback_parallel_begin, ompt_callback_parallel_begin_t, 3) /* parallel begin */ \
|
109 |
+
macro (ompt_callback_parallel_end, ompt_callback_parallel_end_t, 4) /* parallel end */ \
|
110 |
+
\
|
111 |
+
macro (ompt_callback_task_create, ompt_callback_task_create_t, 5) /* task begin */ \
|
112 |
+
macro (ompt_callback_task_schedule, ompt_callback_task_schedule_t, 6) /* task schedule */ \
|
113 |
+
macro (ompt_callback_implicit_task, ompt_callback_implicit_task_t, 7) /* implicit task */ \
|
114 |
+
\
|
115 |
+
macro (ompt_callback_target, ompt_callback_target_t, 8) /* target */ \
|
116 |
+
macro (ompt_callback_target_data_op, ompt_callback_target_data_op_t, 9) /* target data op */ \
|
117 |
+
macro (ompt_callback_target_submit, ompt_callback_target_submit_t, 10) /* target submit */ \
|
118 |
+
\
|
119 |
+
macro (ompt_callback_control_tool, ompt_callback_control_tool_t, 11) /* control tool */ \
|
120 |
+
\
|
121 |
+
macro (ompt_callback_device_initialize, ompt_callback_device_initialize_t, 12) /* device initialize */ \
|
122 |
+
macro (ompt_callback_device_finalize, ompt_callback_device_finalize_t, 13) /* device finalize */ \
|
123 |
+
\
|
124 |
+
macro (ompt_callback_device_load, ompt_callback_device_load_t, 14) /* device load */ \
|
125 |
+
macro (ompt_callback_device_unload, ompt_callback_device_unload_t, 15) /* device unload */ \
|
126 |
+
\
|
127 |
+
/* Optional Events */ \
|
128 |
+
macro (ompt_callback_sync_region_wait, ompt_callback_sync_region_t, 16) /* sync region wait begin or end */ \
|
129 |
+
\
|
130 |
+
macro (ompt_callback_mutex_released, ompt_callback_mutex_t, 17) /* mutex released */ \
|
131 |
+
\
|
132 |
+
macro (ompt_callback_dependences, ompt_callback_dependences_t, 18) /* report task dependences */ \
|
133 |
+
macro (ompt_callback_task_dependence, ompt_callback_task_dependence_t, 19) /* report task dependence */ \
|
134 |
+
\
|
135 |
+
macro (ompt_callback_work, ompt_callback_work_t, 20) /* task at work begin or end */ \
|
136 |
+
\
|
137 |
+
macro (ompt_callback_master, ompt_callback_master_t, 21) /* task at master begin or end */ \
|
138 |
+
\
|
139 |
+
macro (ompt_callback_target_map, ompt_callback_target_map_t, 22) /* target map */ \
|
140 |
+
\
|
141 |
+
macro (ompt_callback_sync_region, ompt_callback_sync_region_t, 23) /* sync region begin or end */ \
|
142 |
+
\
|
143 |
+
macro (ompt_callback_lock_init, ompt_callback_mutex_acquire_t, 24) /* lock init */ \
|
144 |
+
macro (ompt_callback_lock_destroy, ompt_callback_mutex_t, 25) /* lock destroy */ \
|
145 |
+
\
|
146 |
+
macro (ompt_callback_mutex_acquire, ompt_callback_mutex_acquire_t, 26) /* mutex acquire */ \
|
147 |
+
macro (ompt_callback_mutex_acquired, ompt_callback_mutex_t, 27) /* mutex acquired */ \
|
148 |
+
\
|
149 |
+
macro (ompt_callback_nest_lock, ompt_callback_nest_lock_t, 28) /* nest lock */ \
|
150 |
+
\
|
151 |
+
macro (ompt_callback_flush, ompt_callback_flush_t, 29) /* after executing flush */ \
|
152 |
+
\
|
153 |
+
macro (ompt_callback_cancel, ompt_callback_cancel_t, 30) /* cancel innermost binding region */ \
|
154 |
+
\
|
155 |
+
macro (ompt_callback_reduction, ompt_callback_sync_region_t, 31) /* reduction */ \
|
156 |
+
\
|
157 |
+
macro (ompt_callback_dispatch, ompt_callback_dispatch_t, 32) /* dispatch of work */
|
158 |
+
|
159 |
+
/*****************************************************************************
|
160 |
+
* implementation specific types
|
161 |
+
*****************************************************************************/
|
162 |
+
|
163 |
+
typedef enum kmp_mutex_impl_t {
|
164 |
+
#define kmp_mutex_impl_macro(impl, code) impl = code,
|
165 |
+
FOREACH_KMP_MUTEX_IMPL(kmp_mutex_impl_macro)
|
166 |
+
#undef kmp_mutex_impl_macro
|
167 |
+
} kmp_mutex_impl_t;
|
168 |
+
|
169 |
+
/*****************************************************************************
|
170 |
+
* definitions generated from spec
|
171 |
+
*****************************************************************************/
|
172 |
+
|
173 |
+
typedef enum ompt_callbacks_t {
|
174 |
+
ompt_callback_thread_begin = 1,
|
175 |
+
ompt_callback_thread_end = 2,
|
176 |
+
ompt_callback_parallel_begin = 3,
|
177 |
+
ompt_callback_parallel_end = 4,
|
178 |
+
ompt_callback_task_create = 5,
|
179 |
+
ompt_callback_task_schedule = 6,
|
180 |
+
ompt_callback_implicit_task = 7,
|
181 |
+
ompt_callback_target = 8,
|
182 |
+
ompt_callback_target_data_op = 9,
|
183 |
+
ompt_callback_target_submit = 10,
|
184 |
+
ompt_callback_control_tool = 11,
|
185 |
+
ompt_callback_device_initialize = 12,
|
186 |
+
ompt_callback_device_finalize = 13,
|
187 |
+
ompt_callback_device_load = 14,
|
188 |
+
ompt_callback_device_unload = 15,
|
189 |
+
ompt_callback_sync_region_wait = 16,
|
190 |
+
ompt_callback_mutex_released = 17,
|
191 |
+
ompt_callback_dependences = 18,
|
192 |
+
ompt_callback_task_dependence = 19,
|
193 |
+
ompt_callback_work = 20,
|
194 |
+
ompt_callback_master = 21,
|
195 |
+
ompt_callback_target_map = 22,
|
196 |
+
ompt_callback_sync_region = 23,
|
197 |
+
ompt_callback_lock_init = 24,
|
198 |
+
ompt_callback_lock_destroy = 25,
|
199 |
+
ompt_callback_mutex_acquire = 26,
|
200 |
+
ompt_callback_mutex_acquired = 27,
|
201 |
+
ompt_callback_nest_lock = 28,
|
202 |
+
ompt_callback_flush = 29,
|
203 |
+
ompt_callback_cancel = 30,
|
204 |
+
ompt_callback_reduction = 31,
|
205 |
+
ompt_callback_dispatch = 32
|
206 |
+
} ompt_callbacks_t;
|
207 |
+
|
208 |
+
typedef enum ompt_record_t {
|
209 |
+
ompt_record_ompt = 1,
|
210 |
+
ompt_record_native = 2,
|
211 |
+
ompt_record_invalid = 3
|
212 |
+
} ompt_record_t;
|
213 |
+
|
214 |
+
typedef enum ompt_record_native_t {
|
215 |
+
ompt_record_native_info = 1,
|
216 |
+
ompt_record_native_event = 2
|
217 |
+
} ompt_record_native_t;
|
218 |
+
|
219 |
+
typedef enum ompt_set_result_t {
|
220 |
+
ompt_set_error = 0,
|
221 |
+
ompt_set_never = 1,
|
222 |
+
ompt_set_impossible = 2,
|
223 |
+
ompt_set_sometimes = 3,
|
224 |
+
ompt_set_sometimes_paired = 4,
|
225 |
+
ompt_set_always = 5
|
226 |
+
} ompt_set_result_t;
|
227 |
+
|
228 |
+
typedef uint64_t ompt_id_t;
|
229 |
+
|
230 |
+
typedef uint64_t ompt_device_time_t;
|
231 |
+
|
232 |
+
typedef uint64_t ompt_buffer_cursor_t;
|
233 |
+
|
234 |
+
typedef enum ompt_thread_t {
|
235 |
+
ompt_thread_initial = 1,
|
236 |
+
ompt_thread_worker = 2,
|
237 |
+
ompt_thread_other = 3,
|
238 |
+
ompt_thread_unknown = 4
|
239 |
+
} ompt_thread_t;
|
240 |
+
|
241 |
+
typedef enum ompt_scope_endpoint_t {
|
242 |
+
ompt_scope_begin = 1,
|
243 |
+
ompt_scope_end = 2
|
244 |
+
} ompt_scope_endpoint_t;
|
245 |
+
|
246 |
+
typedef enum ompt_dispatch_t {
|
247 |
+
ompt_dispatch_iteration = 1,
|
248 |
+
ompt_dispatch_section = 2
|
249 |
+
} ompt_dispatch_t;
|
250 |
+
|
251 |
+
typedef enum ompt_sync_region_t {
|
252 |
+
ompt_sync_region_barrier = 1,
|
253 |
+
ompt_sync_region_barrier_implicit = 2,
|
254 |
+
ompt_sync_region_barrier_explicit = 3,
|
255 |
+
ompt_sync_region_barrier_implementation = 4,
|
256 |
+
ompt_sync_region_taskwait = 5,
|
257 |
+
ompt_sync_region_taskgroup = 6,
|
258 |
+
ompt_sync_region_reduction = 7
|
259 |
+
} ompt_sync_region_t;
|
260 |
+
|
261 |
+
typedef enum ompt_target_data_op_t {
|
262 |
+
ompt_target_data_alloc = 1,
|
263 |
+
ompt_target_data_transfer_to_device = 2,
|
264 |
+
ompt_target_data_transfer_from_device = 3,
|
265 |
+
ompt_target_data_delete = 4,
|
266 |
+
ompt_target_data_associate = 5,
|
267 |
+
ompt_target_data_disassociate = 6
|
268 |
+
} ompt_target_data_op_t;
|
269 |
+
|
270 |
+
typedef enum ompt_work_t {
|
271 |
+
ompt_work_loop = 1,
|
272 |
+
ompt_work_sections = 2,
|
273 |
+
ompt_work_single_executor = 3,
|
274 |
+
ompt_work_single_other = 4,
|
275 |
+
ompt_work_workshare = 5,
|
276 |
+
ompt_work_distribute = 6,
|
277 |
+
ompt_work_taskloop = 7
|
278 |
+
} ompt_work_t;
|
279 |
+
|
280 |
+
typedef enum ompt_mutex_t {
|
281 |
+
ompt_mutex_lock = 1,
|
282 |
+
ompt_mutex_test_lock = 2,
|
283 |
+
ompt_mutex_nest_lock = 3,
|
284 |
+
ompt_mutex_test_nest_lock = 4,
|
285 |
+
ompt_mutex_critical = 5,
|
286 |
+
ompt_mutex_atomic = 6,
|
287 |
+
ompt_mutex_ordered = 7
|
288 |
+
} ompt_mutex_t;
|
289 |
+
|
290 |
+
typedef enum ompt_native_mon_flag_t {
|
291 |
+
ompt_native_data_motion_explicit = 0x01,
|
292 |
+
ompt_native_data_motion_implicit = 0x02,
|
293 |
+
ompt_native_kernel_invocation = 0x04,
|
294 |
+
ompt_native_kernel_execution = 0x08,
|
295 |
+
ompt_native_driver = 0x10,
|
296 |
+
ompt_native_runtime = 0x20,
|
297 |
+
ompt_native_overhead = 0x40,
|
298 |
+
ompt_native_idleness = 0x80
|
299 |
+
} ompt_native_mon_flag_t;
|
300 |
+
|
301 |
+
typedef enum ompt_task_flag_t {
|
302 |
+
ompt_task_initial = 0x00000001,
|
303 |
+
ompt_task_implicit = 0x00000002,
|
304 |
+
ompt_task_explicit = 0x00000004,
|
305 |
+
ompt_task_target = 0x00000008,
|
306 |
+
ompt_task_undeferred = 0x08000000,
|
307 |
+
ompt_task_untied = 0x10000000,
|
308 |
+
ompt_task_final = 0x20000000,
|
309 |
+
ompt_task_mergeable = 0x40000000,
|
310 |
+
ompt_task_merged = 0x80000000
|
311 |
+
} ompt_task_flag_t;
|
312 |
+
|
313 |
+
typedef enum ompt_task_status_t {
|
314 |
+
ompt_task_complete = 1,
|
315 |
+
ompt_task_yield = 2,
|
316 |
+
ompt_task_cancel = 3,
|
317 |
+
ompt_task_detach = 4,
|
318 |
+
ompt_task_early_fulfill = 5,
|
319 |
+
ompt_task_late_fulfill = 6,
|
320 |
+
ompt_task_switch = 7
|
321 |
+
} ompt_task_status_t;
|
322 |
+
|
323 |
+
typedef enum ompt_target_t {
|
324 |
+
ompt_target = 1,
|
325 |
+
ompt_target_enter_data = 2,
|
326 |
+
ompt_target_exit_data = 3,
|
327 |
+
ompt_target_update = 4
|
328 |
+
} ompt_target_t;
|
329 |
+
|
330 |
+
typedef enum ompt_parallel_flag_t {
|
331 |
+
ompt_parallel_invoker_program = 0x00000001,
|
332 |
+
ompt_parallel_invoker_runtime = 0x00000002,
|
333 |
+
ompt_parallel_league = 0x40000000,
|
334 |
+
ompt_parallel_team = 0x80000000
|
335 |
+
} ompt_parallel_flag_t;
|
336 |
+
|
337 |
+
typedef enum ompt_target_map_flag_t {
|
338 |
+
ompt_target_map_flag_to = 0x01,
|
339 |
+
ompt_target_map_flag_from = 0x02,
|
340 |
+
ompt_target_map_flag_alloc = 0x04,
|
341 |
+
ompt_target_map_flag_release = 0x08,
|
342 |
+
ompt_target_map_flag_delete = 0x10,
|
343 |
+
ompt_target_map_flag_implicit = 0x20
|
344 |
+
} ompt_target_map_flag_t;
|
345 |
+
|
346 |
+
typedef enum ompt_dependence_type_t {
|
347 |
+
ompt_dependence_type_in = 1,
|
348 |
+
ompt_dependence_type_out = 2,
|
349 |
+
ompt_dependence_type_inout = 3,
|
350 |
+
ompt_dependence_type_mutexinoutset = 4,
|
351 |
+
ompt_dependence_type_source = 5,
|
352 |
+
ompt_dependence_type_sink = 6
|
353 |
+
} ompt_dependence_type_t;
|
354 |
+
|
355 |
+
typedef enum ompt_cancel_flag_t {
|
356 |
+
ompt_cancel_parallel = 0x01,
|
357 |
+
ompt_cancel_sections = 0x02,
|
358 |
+
ompt_cancel_loop = 0x04,
|
359 |
+
ompt_cancel_taskgroup = 0x08,
|
360 |
+
ompt_cancel_activated = 0x10,
|
361 |
+
ompt_cancel_detected = 0x20,
|
362 |
+
ompt_cancel_discarded_task = 0x40
|
363 |
+
} ompt_cancel_flag_t;
|
364 |
+
|
365 |
+
typedef uint64_t ompt_hwid_t;
|
366 |
+
|
367 |
+
typedef uint64_t ompt_wait_id_t;
|
368 |
+
|
369 |
+
typedef enum ompt_frame_flag_t {
|
370 |
+
ompt_frame_runtime = 0x00,
|
371 |
+
ompt_frame_application = 0x01,
|
372 |
+
ompt_frame_cfa = 0x10,
|
373 |
+
ompt_frame_framepointer = 0x20,
|
374 |
+
ompt_frame_stackaddress = 0x30
|
375 |
+
} ompt_frame_flag_t;
|
376 |
+
|
377 |
+
typedef enum ompt_state_t {
|
378 |
+
ompt_state_work_serial = 0x000,
|
379 |
+
ompt_state_work_parallel = 0x001,
|
380 |
+
ompt_state_work_reduction = 0x002,
|
381 |
+
|
382 |
+
ompt_state_wait_barrier = 0x010,
|
383 |
+
ompt_state_wait_barrier_implicit_parallel = 0x011,
|
384 |
+
ompt_state_wait_barrier_implicit_workshare = 0x012,
|
385 |
+
ompt_state_wait_barrier_implicit = 0x013,
|
386 |
+
ompt_state_wait_barrier_explicit = 0x014,
|
387 |
+
|
388 |
+
ompt_state_wait_taskwait = 0x020,
|
389 |
+
ompt_state_wait_taskgroup = 0x021,
|
390 |
+
|
391 |
+
ompt_state_wait_mutex = 0x040,
|
392 |
+
ompt_state_wait_lock = 0x041,
|
393 |
+
ompt_state_wait_critical = 0x042,
|
394 |
+
ompt_state_wait_atomic = 0x043,
|
395 |
+
ompt_state_wait_ordered = 0x044,
|
396 |
+
|
397 |
+
ompt_state_wait_target = 0x080,
|
398 |
+
ompt_state_wait_target_map = 0x081,
|
399 |
+
ompt_state_wait_target_update = 0x082,
|
400 |
+
|
401 |
+
ompt_state_idle = 0x100,
|
402 |
+
ompt_state_overhead = 0x101,
|
403 |
+
ompt_state_undefined = 0x102
|
404 |
+
} ompt_state_t;
|
405 |
+
|
406 |
+
typedef uint64_t (*ompt_get_unique_id_t) (void);
|
407 |
+
|
408 |
+
typedef uint64_t ompd_size_t;
|
409 |
+
|
410 |
+
typedef uint64_t ompd_wait_id_t;
|
411 |
+
|
412 |
+
typedef uint64_t ompd_addr_t;
|
413 |
+
typedef int64_t ompd_word_t;
|
414 |
+
typedef uint64_t ompd_seg_t;
|
415 |
+
|
416 |
+
typedef uint64_t ompd_device_t;
|
417 |
+
|
418 |
+
typedef uint64_t ompd_thread_id_t;
|
419 |
+
|
420 |
+
typedef enum ompd_scope_t {
|
421 |
+
ompd_scope_global = 1,
|
422 |
+
ompd_scope_address_space = 2,
|
423 |
+
ompd_scope_thread = 3,
|
424 |
+
ompd_scope_parallel = 4,
|
425 |
+
ompd_scope_implicit_task = 5,
|
426 |
+
ompd_scope_task = 6
|
427 |
+
} ompd_scope_t;
|
428 |
+
|
429 |
+
typedef uint64_t ompd_icv_id_t;
|
430 |
+
|
431 |
+
typedef enum ompd_rc_t {
|
432 |
+
ompd_rc_ok = 0,
|
433 |
+
ompd_rc_unavailable = 1,
|
434 |
+
ompd_rc_stale_handle = 2,
|
435 |
+
ompd_rc_bad_input = 3,
|
436 |
+
ompd_rc_error = 4,
|
437 |
+
ompd_rc_unsupported = 5,
|
438 |
+
ompd_rc_needs_state_tracking = 6,
|
439 |
+
ompd_rc_incompatible = 7,
|
440 |
+
ompd_rc_device_read_error = 8,
|
441 |
+
ompd_rc_device_write_error = 9,
|
442 |
+
ompd_rc_nomem = 10,
|
443 |
+
} ompd_rc_t;
|
444 |
+
|
445 |
+
typedef void (*ompt_interface_fn_t) (void);
|
446 |
+
|
447 |
+
typedef ompt_interface_fn_t (*ompt_function_lookup_t) (
|
448 |
+
const char *interface_function_name
|
449 |
+
);
|
450 |
+
|
451 |
+
typedef union ompt_data_t {
|
452 |
+
uint64_t value;
|
453 |
+
void *ptr;
|
454 |
+
} ompt_data_t;
|
455 |
+
|
456 |
+
typedef struct ompt_frame_t {
|
457 |
+
ompt_data_t exit_frame;
|
458 |
+
ompt_data_t enter_frame;
|
459 |
+
int exit_frame_flags;
|
460 |
+
int enter_frame_flags;
|
461 |
+
} ompt_frame_t;
|
462 |
+
|
463 |
+
typedef void (*ompt_callback_t) (void);
|
464 |
+
|
465 |
+
typedef void ompt_device_t;
|
466 |
+
|
467 |
+
typedef void ompt_buffer_t;
|
468 |
+
|
469 |
+
typedef void (*ompt_callback_buffer_request_t) (
|
470 |
+
int device_num,
|
471 |
+
ompt_buffer_t **buffer,
|
472 |
+
size_t *bytes
|
473 |
+
);
|
474 |
+
|
475 |
+
typedef void (*ompt_callback_buffer_complete_t) (
|
476 |
+
int device_num,
|
477 |
+
ompt_buffer_t *buffer,
|
478 |
+
size_t bytes,
|
479 |
+
ompt_buffer_cursor_t begin,
|
480 |
+
int buffer_owned
|
481 |
+
);
|
482 |
+
|
483 |
+
typedef void (*ompt_finalize_t) (
|
484 |
+
ompt_data_t *tool_data
|
485 |
+
);
|
486 |
+
|
487 |
+
typedef int (*ompt_initialize_t) (
|
488 |
+
ompt_function_lookup_t lookup,
|
489 |
+
int initial_device_num,
|
490 |
+
ompt_data_t *tool_data
|
491 |
+
);
|
492 |
+
|
493 |
+
typedef struct ompt_start_tool_result_t {
|
494 |
+
ompt_initialize_t initialize;
|
495 |
+
ompt_finalize_t finalize;
|
496 |
+
ompt_data_t tool_data;
|
497 |
+
} ompt_start_tool_result_t;
|
498 |
+
|
499 |
+
typedef struct ompt_record_abstract_t {
|
500 |
+
ompt_record_native_t rclass;
|
501 |
+
const char *type;
|
502 |
+
ompt_device_time_t start_time;
|
503 |
+
ompt_device_time_t end_time;
|
504 |
+
ompt_hwid_t hwid;
|
505 |
+
} ompt_record_abstract_t;
|
506 |
+
|
507 |
+
typedef struct ompt_dependence_t {
|
508 |
+
ompt_data_t variable;
|
509 |
+
ompt_dependence_type_t dependence_type;
|
510 |
+
} ompt_dependence_t;
|
511 |
+
|
512 |
+
typedef int (*ompt_enumerate_states_t) (
|
513 |
+
int current_state,
|
514 |
+
int *next_state,
|
515 |
+
const char **next_state_name
|
516 |
+
);
|
517 |
+
|
518 |
+
typedef int (*ompt_enumerate_mutex_impls_t) (
|
519 |
+
int current_impl,
|
520 |
+
int *next_impl,
|
521 |
+
const char **next_impl_name
|
522 |
+
);
|
523 |
+
|
524 |
+
typedef ompt_set_result_t (*ompt_set_callback_t) (
|
525 |
+
ompt_callbacks_t event,
|
526 |
+
ompt_callback_t callback
|
527 |
+
);
|
528 |
+
|
529 |
+
typedef int (*ompt_get_callback_t) (
|
530 |
+
ompt_callbacks_t event,
|
531 |
+
ompt_callback_t *callback
|
532 |
+
);
|
533 |
+
|
534 |
+
typedef ompt_data_t *(*ompt_get_thread_data_t) (void);
|
535 |
+
|
536 |
+
typedef int (*ompt_get_num_procs_t) (void);
|
537 |
+
|
538 |
+
typedef int (*ompt_get_num_places_t) (void);
|
539 |
+
|
540 |
+
typedef int (*ompt_get_place_proc_ids_t) (
|
541 |
+
int place_num,
|
542 |
+
int ids_size,
|
543 |
+
int *ids
|
544 |
+
);
|
545 |
+
|
546 |
+
typedef int (*ompt_get_place_num_t) (void);
|
547 |
+
|
548 |
+
typedef int (*ompt_get_partition_place_nums_t) (
|
549 |
+
int place_nums_size,
|
550 |
+
int *place_nums
|
551 |
+
);
|
552 |
+
|
553 |
+
typedef int (*ompt_get_proc_id_t) (void);
|
554 |
+
|
555 |
+
typedef int (*ompt_get_state_t) (
|
556 |
+
ompt_wait_id_t *wait_id
|
557 |
+
);
|
558 |
+
|
559 |
+
typedef int (*ompt_get_parallel_info_t) (
|
560 |
+
int ancestor_level,
|
561 |
+
ompt_data_t **parallel_data,
|
562 |
+
int *team_size
|
563 |
+
);
|
564 |
+
|
565 |
+
typedef int (*ompt_get_task_info_t) (
|
566 |
+
int ancestor_level,
|
567 |
+
int *flags,
|
568 |
+
ompt_data_t **task_data,
|
569 |
+
ompt_frame_t **task_frame,
|
570 |
+
ompt_data_t **parallel_data,
|
571 |
+
int *thread_num
|
572 |
+
);
|
573 |
+
|
574 |
+
typedef int (*ompt_get_task_memory_t)(
|
575 |
+
void **addr,
|
576 |
+
size_t *size,
|
577 |
+
int block
|
578 |
+
);
|
579 |
+
|
580 |
+
typedef int (*ompt_get_target_info_t) (
|
581 |
+
uint64_t *device_num,
|
582 |
+
ompt_id_t *target_id,
|
583 |
+
ompt_id_t *host_op_id
|
584 |
+
);
|
585 |
+
|
586 |
+
typedef int (*ompt_get_num_devices_t) (void);
|
587 |
+
|
588 |
+
typedef void (*ompt_finalize_tool_t) (void);
|
589 |
+
|
590 |
+
typedef int (*ompt_get_device_num_procs_t) (
|
591 |
+
ompt_device_t *device
|
592 |
+
);
|
593 |
+
|
594 |
+
typedef ompt_device_time_t (*ompt_get_device_time_t) (
|
595 |
+
ompt_device_t *device
|
596 |
+
);
|
597 |
+
|
598 |
+
typedef double (*ompt_translate_time_t) (
|
599 |
+
ompt_device_t *device,
|
600 |
+
ompt_device_time_t time
|
601 |
+
);
|
602 |
+
|
603 |
+
typedef ompt_set_result_t (*ompt_set_trace_ompt_t) (
|
604 |
+
ompt_device_t *device,
|
605 |
+
unsigned int enable,
|
606 |
+
unsigned int etype
|
607 |
+
);
|
608 |
+
|
609 |
+
typedef ompt_set_result_t (*ompt_set_trace_native_t) (
|
610 |
+
ompt_device_t *device,
|
611 |
+
int enable,
|
612 |
+
int flags
|
613 |
+
);
|
614 |
+
|
615 |
+
typedef int (*ompt_start_trace_t) (
|
616 |
+
ompt_device_t *device,
|
617 |
+
ompt_callback_buffer_request_t request,
|
618 |
+
ompt_callback_buffer_complete_t complete
|
619 |
+
);
|
620 |
+
|
621 |
+
typedef int (*ompt_pause_trace_t) (
|
622 |
+
ompt_device_t *device,
|
623 |
+
int begin_pause
|
624 |
+
);
|
625 |
+
|
626 |
+
typedef int (*ompt_flush_trace_t) (
|
627 |
+
ompt_device_t *device
|
628 |
+
);
|
629 |
+
|
630 |
+
typedef int (*ompt_stop_trace_t) (
|
631 |
+
ompt_device_t *device
|
632 |
+
);
|
633 |
+
|
634 |
+
typedef int (*ompt_advance_buffer_cursor_t) (
|
635 |
+
ompt_device_t *device,
|
636 |
+
ompt_buffer_t *buffer,
|
637 |
+
size_t size,
|
638 |
+
ompt_buffer_cursor_t current,
|
639 |
+
ompt_buffer_cursor_t *next
|
640 |
+
);
|
641 |
+
|
642 |
+
typedef ompt_record_t (*ompt_get_record_type_t) (
|
643 |
+
ompt_buffer_t *buffer,
|
644 |
+
ompt_buffer_cursor_t current
|
645 |
+
);
|
646 |
+
|
647 |
+
typedef void *(*ompt_get_record_native_t) (
|
648 |
+
ompt_buffer_t *buffer,
|
649 |
+
ompt_buffer_cursor_t current,
|
650 |
+
ompt_id_t *host_op_id
|
651 |
+
);
|
652 |
+
|
653 |
+
typedef ompt_record_abstract_t *
|
654 |
+
(*ompt_get_record_abstract_t) (
|
655 |
+
void *native_record
|
656 |
+
);
|
657 |
+
|
658 |
+
typedef void (*ompt_callback_thread_begin_t) (
|
659 |
+
ompt_thread_t thread_type,
|
660 |
+
ompt_data_t *thread_data
|
661 |
+
);
|
662 |
+
|
663 |
+
typedef struct ompt_record_thread_begin_t {
|
664 |
+
ompt_thread_t thread_type;
|
665 |
+
} ompt_record_thread_begin_t;
|
666 |
+
|
667 |
+
typedef void (*ompt_callback_thread_end_t) (
|
668 |
+
ompt_data_t *thread_data
|
669 |
+
);
|
670 |
+
|
671 |
+
typedef void (*ompt_callback_parallel_begin_t) (
|
672 |
+
ompt_data_t *encountering_task_data,
|
673 |
+
const ompt_frame_t *encountering_task_frame,
|
674 |
+
ompt_data_t *parallel_data,
|
675 |
+
unsigned int requested_parallelism,
|
676 |
+
int flags,
|
677 |
+
const void *codeptr_ra
|
678 |
+
);
|
679 |
+
|
680 |
+
typedef struct ompt_record_parallel_begin_t {
|
681 |
+
ompt_id_t encountering_task_id;
|
682 |
+
ompt_id_t parallel_id;
|
683 |
+
unsigned int requested_parallelism;
|
684 |
+
int flags;
|
685 |
+
const void *codeptr_ra;
|
686 |
+
} ompt_record_parallel_begin_t;
|
687 |
+
|
688 |
+
typedef void (*ompt_callback_parallel_end_t) (
|
689 |
+
ompt_data_t *parallel_data,
|
690 |
+
ompt_data_t *encountering_task_data,
|
691 |
+
int flags,
|
692 |
+
const void *codeptr_ra
|
693 |
+
);
|
694 |
+
|
695 |
+
typedef struct ompt_record_parallel_end_t {
|
696 |
+
ompt_id_t parallel_id;
|
697 |
+
ompt_id_t encountering_task_id;
|
698 |
+
int flags;
|
699 |
+
const void *codeptr_ra;
|
700 |
+
} ompt_record_parallel_end_t;
|
701 |
+
|
702 |
+
typedef void (*ompt_callback_work_t) (
|
703 |
+
ompt_work_t wstype,
|
704 |
+
ompt_scope_endpoint_t endpoint,
|
705 |
+
ompt_data_t *parallel_data,
|
706 |
+
ompt_data_t *task_data,
|
707 |
+
uint64_t count,
|
708 |
+
const void *codeptr_ra
|
709 |
+
);
|
710 |
+
|
711 |
+
typedef struct ompt_record_work_t {
|
712 |
+
ompt_work_t wstype;
|
713 |
+
ompt_scope_endpoint_t endpoint;
|
714 |
+
ompt_id_t parallel_id;
|
715 |
+
ompt_id_t task_id;
|
716 |
+
uint64_t count;
|
717 |
+
const void *codeptr_ra;
|
718 |
+
} ompt_record_work_t;
|
719 |
+
|
720 |
+
typedef void (*ompt_callback_dispatch_t) (
|
721 |
+
ompt_data_t *parallel_data,
|
722 |
+
ompt_data_t *task_data,
|
723 |
+
ompt_dispatch_t kind,
|
724 |
+
ompt_data_t instance
|
725 |
+
);
|
726 |
+
|
727 |
+
typedef struct ompt_record_dispatch_t {
|
728 |
+
ompt_id_t parallel_id;
|
729 |
+
ompt_id_t task_id;
|
730 |
+
ompt_dispatch_t kind;
|
731 |
+
ompt_data_t instance;
|
732 |
+
} ompt_record_dispatch_t;
|
733 |
+
|
734 |
+
typedef void (*ompt_callback_task_create_t) (
|
735 |
+
ompt_data_t *encountering_task_data,
|
736 |
+
const ompt_frame_t *encountering_task_frame,
|
737 |
+
ompt_data_t *new_task_data,
|
738 |
+
int flags,
|
739 |
+
int has_dependences,
|
740 |
+
const void *codeptr_ra
|
741 |
+
);
|
742 |
+
|
743 |
+
typedef struct ompt_record_task_create_t {
|
744 |
+
ompt_id_t encountering_task_id;
|
745 |
+
ompt_id_t new_task_id;
|
746 |
+
int flags;
|
747 |
+
int has_dependences;
|
748 |
+
const void *codeptr_ra;
|
749 |
+
} ompt_record_task_create_t;
|
750 |
+
|
751 |
+
typedef void (*ompt_callback_dependences_t) (
|
752 |
+
ompt_data_t *task_data,
|
753 |
+
const ompt_dependence_t *deps,
|
754 |
+
int ndeps
|
755 |
+
);
|
756 |
+
|
757 |
+
typedef struct ompt_record_dependences_t {
|
758 |
+
ompt_id_t task_id;
|
759 |
+
ompt_dependence_t dep;
|
760 |
+
int ndeps;
|
761 |
+
} ompt_record_dependences_t;
|
762 |
+
|
763 |
+
typedef void (*ompt_callback_task_dependence_t) (
|
764 |
+
ompt_data_t *src_task_data,
|
765 |
+
ompt_data_t *sink_task_data
|
766 |
+
);
|
767 |
+
|
768 |
+
typedef struct ompt_record_task_dependence_t {
|
769 |
+
ompt_id_t src_task_id;
|
770 |
+
ompt_id_t sink_task_id;
|
771 |
+
} ompt_record_task_dependence_t;
|
772 |
+
|
773 |
+
typedef void (*ompt_callback_task_schedule_t) (
|
774 |
+
ompt_data_t *prior_task_data,
|
775 |
+
ompt_task_status_t prior_task_status,
|
776 |
+
ompt_data_t *next_task_data
|
777 |
+
);
|
778 |
+
|
779 |
+
typedef struct ompt_record_task_schedule_t {
|
780 |
+
ompt_id_t prior_task_id;
|
781 |
+
ompt_task_status_t prior_task_status;
|
782 |
+
ompt_id_t next_task_id;
|
783 |
+
} ompt_record_task_schedule_t;
|
784 |
+
|
785 |
+
typedef void (*ompt_callback_implicit_task_t) (
|
786 |
+
ompt_scope_endpoint_t endpoint,
|
787 |
+
ompt_data_t *parallel_data,
|
788 |
+
ompt_data_t *task_data,
|
789 |
+
unsigned int actual_parallelism,
|
790 |
+
unsigned int index,
|
791 |
+
int flags
|
792 |
+
);
|
793 |
+
|
794 |
+
typedef struct ompt_record_implicit_task_t {
|
795 |
+
ompt_scope_endpoint_t endpoint;
|
796 |
+
ompt_id_t parallel_id;
|
797 |
+
ompt_id_t task_id;
|
798 |
+
unsigned int actual_parallelism;
|
799 |
+
unsigned int index;
|
800 |
+
int flags;
|
801 |
+
} ompt_record_implicit_task_t;
|
802 |
+
|
803 |
+
typedef void (*ompt_callback_master_t) (
|
804 |
+
ompt_scope_endpoint_t endpoint,
|
805 |
+
ompt_data_t *parallel_data,
|
806 |
+
ompt_data_t *task_data,
|
807 |
+
const void *codeptr_ra
|
808 |
+
);
|
809 |
+
|
810 |
+
typedef struct ompt_record_master_t {
|
811 |
+
ompt_scope_endpoint_t endpoint;
|
812 |
+
ompt_id_t parallel_id;
|
813 |
+
ompt_id_t task_id;
|
814 |
+
const void *codeptr_ra;
|
815 |
+
} ompt_record_master_t;
|
816 |
+
|
817 |
+
typedef void (*ompt_callback_sync_region_t) (
|
818 |
+
ompt_sync_region_t kind,
|
819 |
+
ompt_scope_endpoint_t endpoint,
|
820 |
+
ompt_data_t *parallel_data,
|
821 |
+
ompt_data_t *task_data,
|
822 |
+
const void *codeptr_ra
|
823 |
+
);
|
824 |
+
|
825 |
+
typedef struct ompt_record_sync_region_t {
|
826 |
+
ompt_sync_region_t kind;
|
827 |
+
ompt_scope_endpoint_t endpoint;
|
828 |
+
ompt_id_t parallel_id;
|
829 |
+
ompt_id_t task_id;
|
830 |
+
const void *codeptr_ra;
|
831 |
+
} ompt_record_sync_region_t;
|
832 |
+
|
833 |
+
typedef void (*ompt_callback_mutex_acquire_t) (
|
834 |
+
ompt_mutex_t kind,
|
835 |
+
unsigned int hint,
|
836 |
+
unsigned int impl,
|
837 |
+
ompt_wait_id_t wait_id,
|
838 |
+
const void *codeptr_ra
|
839 |
+
);
|
840 |
+
|
841 |
+
typedef struct ompt_record_mutex_acquire_t {
|
842 |
+
ompt_mutex_t kind;
|
843 |
+
unsigned int hint;
|
844 |
+
unsigned int impl;
|
845 |
+
ompt_wait_id_t wait_id;
|
846 |
+
const void *codeptr_ra;
|
847 |
+
} ompt_record_mutex_acquire_t;
|
848 |
+
|
849 |
+
typedef void (*ompt_callback_mutex_t) (
|
850 |
+
ompt_mutex_t kind,
|
851 |
+
ompt_wait_id_t wait_id,
|
852 |
+
const void *codeptr_ra
|
853 |
+
);
|
854 |
+
|
855 |
+
typedef struct ompt_record_mutex_t {
|
856 |
+
ompt_mutex_t kind;
|
857 |
+
ompt_wait_id_t wait_id;
|
858 |
+
const void *codeptr_ra;
|
859 |
+
} ompt_record_mutex_t;
|
860 |
+
|
861 |
+
typedef void (*ompt_callback_nest_lock_t) (
|
862 |
+
ompt_scope_endpoint_t endpoint,
|
863 |
+
ompt_wait_id_t wait_id,
|
864 |
+
const void *codeptr_ra
|
865 |
+
);
|
866 |
+
|
867 |
+
typedef struct ompt_record_nest_lock_t {
|
868 |
+
ompt_scope_endpoint_t endpoint;
|
869 |
+
ompt_wait_id_t wait_id;
|
870 |
+
const void *codeptr_ra;
|
871 |
+
} ompt_record_nest_lock_t;
|
872 |
+
|
873 |
+
typedef void (*ompt_callback_flush_t) (
|
874 |
+
ompt_data_t *thread_data,
|
875 |
+
const void *codeptr_ra
|
876 |
+
);
|
877 |
+
|
878 |
+
typedef struct ompt_record_flush_t {
|
879 |
+
const void *codeptr_ra;
|
880 |
+
} ompt_record_flush_t;
|
881 |
+
|
882 |
+
typedef void (*ompt_callback_cancel_t) (
|
883 |
+
ompt_data_t *task_data,
|
884 |
+
int flags,
|
885 |
+
const void *codeptr_ra
|
886 |
+
);
|
887 |
+
|
888 |
+
typedef struct ompt_record_cancel_t {
|
889 |
+
ompt_id_t task_id;
|
890 |
+
int flags;
|
891 |
+
const void *codeptr_ra;
|
892 |
+
} ompt_record_cancel_t;
|
893 |
+
|
894 |
+
typedef void (*ompt_callback_device_initialize_t) (
|
895 |
+
int device_num,
|
896 |
+
const char *type,
|
897 |
+
ompt_device_t *device,
|
898 |
+
ompt_function_lookup_t lookup,
|
899 |
+
const char *documentation
|
900 |
+
);
|
901 |
+
|
902 |
+
typedef void (*ompt_callback_device_finalize_t) (
|
903 |
+
int device_num
|
904 |
+
);
|
905 |
+
|
906 |
+
typedef void (*ompt_callback_device_load_t) (
|
907 |
+
int device_num,
|
908 |
+
const char *filename,
|
909 |
+
int64_t offset_in_file,
|
910 |
+
void *vma_in_file,
|
911 |
+
size_t bytes,
|
912 |
+
void *host_addr,
|
913 |
+
void *device_addr,
|
914 |
+
uint64_t module_id
|
915 |
+
);
|
916 |
+
|
917 |
+
typedef void (*ompt_callback_device_unload_t) (
|
918 |
+
int device_num,
|
919 |
+
uint64_t module_id
|
920 |
+
);
|
921 |
+
|
922 |
+
typedef void (*ompt_callback_target_data_op_t) (
|
923 |
+
ompt_id_t target_id,
|
924 |
+
ompt_id_t host_op_id,
|
925 |
+
ompt_target_data_op_t optype,
|
926 |
+
void *src_addr,
|
927 |
+
int src_device_num,
|
928 |
+
void *dest_addr,
|
929 |
+
int dest_device_num,
|
930 |
+
size_t bytes,
|
931 |
+
const void *codeptr_ra
|
932 |
+
);
|
933 |
+
|
934 |
+
typedef struct ompt_record_target_data_op_t {
|
935 |
+
ompt_id_t host_op_id;
|
936 |
+
ompt_target_data_op_t optype;
|
937 |
+
void *src_addr;
|
938 |
+
int src_device_num;
|
939 |
+
void *dest_addr;
|
940 |
+
int dest_device_num;
|
941 |
+
size_t bytes;
|
942 |
+
ompt_device_time_t end_time;
|
943 |
+
const void *codeptr_ra;
|
944 |
+
} ompt_record_target_data_op_t;
|
945 |
+
|
946 |
+
typedef void (*ompt_callback_target_t) (
|
947 |
+
ompt_target_t kind,
|
948 |
+
ompt_scope_endpoint_t endpoint,
|
949 |
+
int device_num,
|
950 |
+
ompt_data_t *task_data,
|
951 |
+
ompt_id_t target_id,
|
952 |
+
const void *codeptr_ra
|
953 |
+
);
|
954 |
+
|
955 |
+
typedef struct ompt_record_target_t {
|
956 |
+
ompt_target_t kind;
|
957 |
+
ompt_scope_endpoint_t endpoint;
|
958 |
+
int device_num;
|
959 |
+
ompt_id_t task_id;
|
960 |
+
ompt_id_t target_id;
|
961 |
+
const void *codeptr_ra;
|
962 |
+
} ompt_record_target_t;
|
963 |
+
|
964 |
+
typedef void (*ompt_callback_target_map_t) (
|
965 |
+
ompt_id_t target_id,
|
966 |
+
unsigned int nitems,
|
967 |
+
void **host_addr,
|
968 |
+
void **device_addr,
|
969 |
+
size_t *bytes,
|
970 |
+
unsigned int *mapping_flags,
|
971 |
+
const void *codeptr_ra
|
972 |
+
);
|
973 |
+
|
974 |
+
typedef struct ompt_record_target_map_t {
|
975 |
+
ompt_id_t target_id;
|
976 |
+
unsigned int nitems;
|
977 |
+
void **host_addr;
|
978 |
+
void **device_addr;
|
979 |
+
size_t *bytes;
|
980 |
+
unsigned int *mapping_flags;
|
981 |
+
const void *codeptr_ra;
|
982 |
+
} ompt_record_target_map_t;
|
983 |
+
|
984 |
+
typedef void (*ompt_callback_target_submit_t) (
|
985 |
+
ompt_id_t target_id,
|
986 |
+
ompt_id_t host_op_id,
|
987 |
+
unsigned int requested_num_teams
|
988 |
+
);
|
989 |
+
|
990 |
+
typedef struct ompt_record_target_kernel_t {
|
991 |
+
ompt_id_t host_op_id;
|
992 |
+
unsigned int requested_num_teams;
|
993 |
+
unsigned int granted_num_teams;
|
994 |
+
ompt_device_time_t end_time;
|
995 |
+
} ompt_record_target_kernel_t;
|
996 |
+
|
997 |
+
typedef int (*ompt_callback_control_tool_t) (
|
998 |
+
uint64_t command,
|
999 |
+
uint64_t modifier,
|
1000 |
+
void *arg,
|
1001 |
+
const void *codeptr_ra
|
1002 |
+
);
|
1003 |
+
|
1004 |
+
typedef struct ompt_record_control_tool_t {
|
1005 |
+
uint64_t command;
|
1006 |
+
uint64_t modifier;
|
1007 |
+
const void *codeptr_ra;
|
1008 |
+
} ompt_record_control_tool_t;
|
1009 |
+
|
1010 |
+
typedef struct ompd_address_t {
|
1011 |
+
ompd_seg_t segment;
|
1012 |
+
ompd_addr_t address;
|
1013 |
+
} ompd_address_t;
|
1014 |
+
|
1015 |
+
typedef struct ompd_frame_info_t {
|
1016 |
+
ompd_address_t frame_address;
|
1017 |
+
ompd_word_t frame_flag;
|
1018 |
+
} ompd_frame_info_t;
|
1019 |
+
|
1020 |
+
typedef struct _ompd_aspace_handle ompd_address_space_handle_t;
|
1021 |
+
typedef struct _ompd_thread_handle ompd_thread_handle_t;
|
1022 |
+
typedef struct _ompd_parallel_handle ompd_parallel_handle_t;
|
1023 |
+
typedef struct _ompd_task_handle ompd_task_handle_t;
|
1024 |
+
|
1025 |
+
typedef struct _ompd_aspace_cont ompd_address_space_context_t;
|
1026 |
+
typedef struct _ompd_thread_cont ompd_thread_context_t;
|
1027 |
+
|
1028 |
+
typedef struct ompd_device_type_sizes_t {
|
1029 |
+
uint8_t sizeof_char;
|
1030 |
+
uint8_t sizeof_short;
|
1031 |
+
uint8_t sizeof_int;
|
1032 |
+
uint8_t sizeof_long;
|
1033 |
+
uint8_t sizeof_long_long;
|
1034 |
+
uint8_t sizeof_pointer;
|
1035 |
+
} ompd_device_type_sizes_t;
|
1036 |
+
|
1037 |
+
typedef struct ompt_record_ompt_t {
|
1038 |
+
ompt_callbacks_t type;
|
1039 |
+
ompt_device_time_t time;
|
1040 |
+
ompt_id_t thread_id;
|
1041 |
+
ompt_id_t target_id;
|
1042 |
+
union {
|
1043 |
+
ompt_record_thread_begin_t thread_begin;
|
1044 |
+
ompt_record_parallel_begin_t parallel_begin;
|
1045 |
+
ompt_record_parallel_end_t parallel_end;
|
1046 |
+
ompt_record_work_t work;
|
1047 |
+
ompt_record_dispatch_t dispatch;
|
1048 |
+
ompt_record_task_create_t task_create;
|
1049 |
+
ompt_record_dependences_t dependences;
|
1050 |
+
ompt_record_task_dependence_t task_dependence;
|
1051 |
+
ompt_record_task_schedule_t task_schedule;
|
1052 |
+
ompt_record_implicit_task_t implicit_task;
|
1053 |
+
ompt_record_master_t master;
|
1054 |
+
ompt_record_sync_region_t sync_region;
|
1055 |
+
ompt_record_mutex_acquire_t mutex_acquire;
|
1056 |
+
ompt_record_mutex_t mutex;
|
1057 |
+
ompt_record_nest_lock_t nest_lock;
|
1058 |
+
ompt_record_flush_t flush;
|
1059 |
+
ompt_record_cancel_t cancel;
|
1060 |
+
ompt_record_target_t target;
|
1061 |
+
ompt_record_target_data_op_t target_data_op;
|
1062 |
+
ompt_record_target_map_t target_map;
|
1063 |
+
ompt_record_target_kernel_t target_kernel;
|
1064 |
+
ompt_record_control_tool_t control_tool;
|
1065 |
+
} record;
|
1066 |
+
} ompt_record_ompt_t;
|
1067 |
+
|
1068 |
+
typedef ompt_record_ompt_t *(*ompt_get_record_ompt_t) (
|
1069 |
+
ompt_buffer_t *buffer,
|
1070 |
+
ompt_buffer_cursor_t current
|
1071 |
+
);
|
1072 |
+
|
1073 |
+
#define ompt_id_none 0
|
1074 |
+
#define ompt_data_none {0}
|
1075 |
+
#define ompt_time_none 0
|
1076 |
+
#define ompt_hwid_none 0
|
1077 |
+
#define ompt_addr_none ~0
|
1078 |
+
#define ompt_mutex_impl_none 0
|
1079 |
+
#define ompt_wait_id_none 0
|
1080 |
+
|
1081 |
+
#define ompd_segment_none 0
|
1082 |
+
|
1083 |
+
#endif /* __OMPT__ */
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/include/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (198 Bytes). View file
|
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libcheckpoint.so
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1626ff119582bca46605bc6d49769ab75314b9993dd647bd64a90dec747bc843
|
3 |
+
size 1534104
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libcupti.so.12
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:abc63100e9cf516b8ed1fa25354ae53dbfe8df4838ac525d8d738332c2198dc2
|
3 |
+
size 7419504
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_cupti/lib/libnvperf_target.so
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:fa2587c8d211fbc85e8b88cca0bcebe78c8cc40c81b0c3763ce57ac9e63f0669
|
3 |
+
size 5895416
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_nvrtc/include/nvrtc.h
ADDED
@@ -0,0 +1,845 @@
|
|
|
|
|
|
|
|
|
|
|
|
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1 |
+
//
|
2 |
+
// NVIDIA_COPYRIGHT_BEGIN
|
3 |
+
//
|
4 |
+
// Copyright (c) 2014-2023, NVIDIA CORPORATION. All rights reserved.
|
5 |
+
//
|
6 |
+
// NVIDIA CORPORATION and its licensors retain all intellectual property
|
7 |
+
// and proprietary rights in and to this software, related documentation
|
8 |
+
// and any modifications thereto. Any use, reproduction, disclosure or
|
9 |
+
// distribution of this software and related documentation without an express
|
10 |
+
// license agreement from NVIDIA CORPORATION is strictly prohibited.
|
11 |
+
//
|
12 |
+
// NVIDIA_COPYRIGHT_END
|
13 |
+
//
|
14 |
+
|
15 |
+
#ifndef __NVRTC_H__
|
16 |
+
#define __NVRTC_H__
|
17 |
+
|
18 |
+
#ifdef __cplusplus
|
19 |
+
extern "C" {
|
20 |
+
#endif /* __cplusplus */
|
21 |
+
|
22 |
+
#include <stdlib.h>
|
23 |
+
|
24 |
+
|
25 |
+
/*************************************************************************//**
|
26 |
+
*
|
27 |
+
* \defgroup error Error Handling
|
28 |
+
*
|
29 |
+
* NVRTC defines the following enumeration type and function for API call
|
30 |
+
* error handling.
|
31 |
+
*
|
32 |
+
****************************************************************************/
|
33 |
+
|
34 |
+
|
35 |
+
/**
|
36 |
+
* \ingroup error
|
37 |
+
* \brief The enumerated type nvrtcResult defines API call result codes.
|
38 |
+
* NVRTC API functions return nvrtcResult to indicate the call
|
39 |
+
* result.
|
40 |
+
*/
|
41 |
+
typedef enum {
|
42 |
+
NVRTC_SUCCESS = 0,
|
43 |
+
NVRTC_ERROR_OUT_OF_MEMORY = 1,
|
44 |
+
NVRTC_ERROR_PROGRAM_CREATION_FAILURE = 2,
|
45 |
+
NVRTC_ERROR_INVALID_INPUT = 3,
|
46 |
+
NVRTC_ERROR_INVALID_PROGRAM = 4,
|
47 |
+
NVRTC_ERROR_INVALID_OPTION = 5,
|
48 |
+
NVRTC_ERROR_COMPILATION = 6,
|
49 |
+
NVRTC_ERROR_BUILTIN_OPERATION_FAILURE = 7,
|
50 |
+
NVRTC_ERROR_NO_NAME_EXPRESSIONS_AFTER_COMPILATION = 8,
|
51 |
+
NVRTC_ERROR_NO_LOWERED_NAMES_BEFORE_COMPILATION = 9,
|
52 |
+
NVRTC_ERROR_NAME_EXPRESSION_NOT_VALID = 10,
|
53 |
+
NVRTC_ERROR_INTERNAL_ERROR = 11,
|
54 |
+
NVRTC_ERROR_TIME_FILE_WRITE_FAILED = 12
|
55 |
+
} nvrtcResult;
|
56 |
+
|
57 |
+
|
58 |
+
/**
|
59 |
+
* \ingroup error
|
60 |
+
* \brief nvrtcGetErrorString is a helper function that returns a string
|
61 |
+
* describing the given nvrtcResult code, e.g., NVRTC_SUCCESS to
|
62 |
+
* \c "NVRTC_SUCCESS".
|
63 |
+
* For unrecognized enumeration values, it returns
|
64 |
+
* \c "NVRTC_ERROR unknown".
|
65 |
+
*
|
66 |
+
* \param [in] result CUDA Runtime Compilation API result code.
|
67 |
+
* \return Message string for the given #nvrtcResult code.
|
68 |
+
*/
|
69 |
+
const char *nvrtcGetErrorString(nvrtcResult result);
|
70 |
+
|
71 |
+
|
72 |
+
/*************************************************************************//**
|
73 |
+
*
|
74 |
+
* \defgroup query General Information Query
|
75 |
+
*
|
76 |
+
* NVRTC defines the following function for general information query.
|
77 |
+
*
|
78 |
+
****************************************************************************/
|
79 |
+
|
80 |
+
|
81 |
+
/**
|
82 |
+
* \ingroup query
|
83 |
+
* \brief nvrtcVersion sets the output parameters \p major and \p minor
|
84 |
+
* with the CUDA Runtime Compilation version number.
|
85 |
+
*
|
86 |
+
* \param [out] major CUDA Runtime Compilation major version number.
|
87 |
+
* \param [out] minor CUDA Runtime Compilation minor version number.
|
88 |
+
* \return
|
89 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
90 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
91 |
+
*
|
92 |
+
*/
|
93 |
+
nvrtcResult nvrtcVersion(int *major, int *minor);
|
94 |
+
|
95 |
+
|
96 |
+
/**
|
97 |
+
* \ingroup query
|
98 |
+
* \brief nvrtcGetNumSupportedArchs sets the output parameter \p numArchs
|
99 |
+
* with the number of architectures supported by NVRTC. This can
|
100 |
+
* then be used to pass an array to ::nvrtcGetSupportedArchs to
|
101 |
+
* get the supported architectures.
|
102 |
+
*
|
103 |
+
* \param [out] numArchs number of supported architectures.
|
104 |
+
* \return
|
105 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
106 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
107 |
+
*
|
108 |
+
* see ::nvrtcGetSupportedArchs
|
109 |
+
*/
|
110 |
+
nvrtcResult nvrtcGetNumSupportedArchs(int* numArchs);
|
111 |
+
|
112 |
+
|
113 |
+
/**
|
114 |
+
* \ingroup query
|
115 |
+
* \brief nvrtcGetSupportedArchs populates the array passed via the output parameter
|
116 |
+
* \p supportedArchs with the architectures supported by NVRTC. The array is
|
117 |
+
* sorted in the ascending order. The size of the array to be passed can be
|
118 |
+
* determined using ::nvrtcGetNumSupportedArchs.
|
119 |
+
*
|
120 |
+
* \param [out] supportedArchs sorted array of supported architectures.
|
121 |
+
* \return
|
122 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
123 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
124 |
+
*
|
125 |
+
* see ::nvrtcGetNumSupportedArchs
|
126 |
+
*/
|
127 |
+
nvrtcResult nvrtcGetSupportedArchs(int* supportedArchs);
|
128 |
+
|
129 |
+
|
130 |
+
/*************************************************************************//**
|
131 |
+
*
|
132 |
+
* \defgroup compilation Compilation
|
133 |
+
*
|
134 |
+
* NVRTC defines the following type and functions for actual compilation.
|
135 |
+
*
|
136 |
+
****************************************************************************/
|
137 |
+
|
138 |
+
|
139 |
+
/**
|
140 |
+
* \ingroup compilation
|
141 |
+
* \brief nvrtcProgram is the unit of compilation, and an opaque handle for
|
142 |
+
* a program.
|
143 |
+
*
|
144 |
+
* To compile a CUDA program string, an instance of nvrtcProgram must be
|
145 |
+
* created first with ::nvrtcCreateProgram, then compiled with
|
146 |
+
* ::nvrtcCompileProgram.
|
147 |
+
*/
|
148 |
+
typedef struct _nvrtcProgram *nvrtcProgram;
|
149 |
+
|
150 |
+
|
151 |
+
/**
|
152 |
+
* \ingroup compilation
|
153 |
+
* \brief nvrtcCreateProgram creates an instance of nvrtcProgram with the
|
154 |
+
* given input parameters, and sets the output parameter \p prog with
|
155 |
+
* it.
|
156 |
+
*
|
157 |
+
* \param [out] prog CUDA Runtime Compilation program.
|
158 |
+
* \param [in] src CUDA program source.
|
159 |
+
* \param [in] name CUDA program name.\n
|
160 |
+
* \p name can be \c NULL; \c "default_program" is
|
161 |
+
* used when \p name is \c NULL or "".
|
162 |
+
* \param [in] numHeaders Number of headers used.\n
|
163 |
+
* \p numHeaders must be greater than or equal to 0.
|
164 |
+
* \param [in] headers Sources of the headers.\n
|
165 |
+
* \p headers can be \c NULL when \p numHeaders is
|
166 |
+
* 0.
|
167 |
+
* \param [in] includeNames Name of each header by which they can be
|
168 |
+
* included in the CUDA program source.\n
|
169 |
+
* \p includeNames can be \c NULL when \p numHeaders
|
170 |
+
* is 0. These headers must be included with the exact
|
171 |
+
* names specified here.
|
172 |
+
* \return
|
173 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
174 |
+
* - \link #nvrtcResult NVRTC_ERROR_OUT_OF_MEMORY \endlink
|
175 |
+
* - \link #nvrtcResult NVRTC_ERROR_PROGRAM_CREATION_FAILURE \endlink
|
176 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
177 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
178 |
+
*
|
179 |
+
* \see ::nvrtcDestroyProgram
|
180 |
+
*/
|
181 |
+
nvrtcResult nvrtcCreateProgram(nvrtcProgram *prog,
|
182 |
+
const char *src,
|
183 |
+
const char *name,
|
184 |
+
int numHeaders,
|
185 |
+
const char * const *headers,
|
186 |
+
const char * const *includeNames);
|
187 |
+
|
188 |
+
|
189 |
+
/**
|
190 |
+
* \ingroup compilation
|
191 |
+
* \brief nvrtcDestroyProgram destroys the given program.
|
192 |
+
*
|
193 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
194 |
+
* \return
|
195 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
196 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
197 |
+
*
|
198 |
+
* \see ::nvrtcCreateProgram
|
199 |
+
*/
|
200 |
+
nvrtcResult nvrtcDestroyProgram(nvrtcProgram *prog);
|
201 |
+
|
202 |
+
|
203 |
+
/**
|
204 |
+
* \ingroup compilation
|
205 |
+
* \brief nvrtcCompileProgram compiles the given program.
|
206 |
+
*
|
207 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
208 |
+
* \param [in] numOptions Number of compiler options passed.
|
209 |
+
* \param [in] options Compiler options in the form of C string array.\n
|
210 |
+
* \p options can be \c NULL when \p numOptions is 0.
|
211 |
+
*
|
212 |
+
* \return
|
213 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
214 |
+
* - \link #nvrtcResult NVRTC_ERROR_OUT_OF_MEMORY \endlink
|
215 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
216 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
217 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_OPTION \endlink
|
218 |
+
* - \link #nvrtcResult NVRTC_ERROR_COMPILATION \endlink
|
219 |
+
* - \link #nvrtcResult NVRTC_ERROR_BUILTIN_OPERATION_FAILURE \endlink
|
220 |
+
* - \link #nvrtcResult NVRTC_ERROR_TIME_FILE_WRITE_FAILED \endlink
|
221 |
+
*
|
222 |
+
* It supports compile options listed in \ref options.
|
223 |
+
*/
|
224 |
+
nvrtcResult nvrtcCompileProgram(nvrtcProgram prog,
|
225 |
+
int numOptions, const char * const *options);
|
226 |
+
|
227 |
+
|
228 |
+
/**
|
229 |
+
* \ingroup compilation
|
230 |
+
* \brief nvrtcGetPTXSize sets the value of \p ptxSizeRet with the size of the PTX
|
231 |
+
* generated by the previous compilation of \p prog (including the
|
232 |
+
* trailing \c NULL).
|
233 |
+
*
|
234 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
235 |
+
* \param [out] ptxSizeRet Size of the generated PTX (including the trailing
|
236 |
+
* \c NULL).
|
237 |
+
* \return
|
238 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
239 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
240 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
241 |
+
*
|
242 |
+
* \see ::nvrtcGetPTX
|
243 |
+
*/
|
244 |
+
nvrtcResult nvrtcGetPTXSize(nvrtcProgram prog, size_t *ptxSizeRet);
|
245 |
+
|
246 |
+
|
247 |
+
/**
|
248 |
+
* \ingroup compilation
|
249 |
+
* \brief nvrtcGetPTX stores the PTX generated by the previous compilation
|
250 |
+
* of \p prog in the memory pointed by \p ptx.
|
251 |
+
*
|
252 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
253 |
+
* \param [out] ptx Compiled result.
|
254 |
+
* \return
|
255 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
256 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
257 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
258 |
+
*
|
259 |
+
* \see ::nvrtcGetPTXSize
|
260 |
+
*/
|
261 |
+
nvrtcResult nvrtcGetPTX(nvrtcProgram prog, char *ptx);
|
262 |
+
|
263 |
+
|
264 |
+
/**
|
265 |
+
* \ingroup compilation
|
266 |
+
* \brief nvrtcGetCUBINSize sets the value of \p cubinSizeRet with the size of the cubin
|
267 |
+
* generated by the previous compilation of \p prog. The value of
|
268 |
+
* cubinSizeRet is set to 0 if the value specified to \c -arch is a
|
269 |
+
* virtual architecture instead of an actual architecture.
|
270 |
+
*
|
271 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
272 |
+
* \param [out] cubinSizeRet Size of the generated cubin.
|
273 |
+
* \return
|
274 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
275 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
276 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
277 |
+
*
|
278 |
+
* \see ::nvrtcGetCUBIN
|
279 |
+
*/
|
280 |
+
nvrtcResult nvrtcGetCUBINSize(nvrtcProgram prog, size_t *cubinSizeRet);
|
281 |
+
|
282 |
+
|
283 |
+
/**
|
284 |
+
* \ingroup compilation
|
285 |
+
* \brief nvrtcGetCUBIN stores the cubin generated by the previous compilation
|
286 |
+
* of \p prog in the memory pointed by \p cubin. No cubin is available
|
287 |
+
* if the value specified to \c -arch is a virtual architecture instead
|
288 |
+
* of an actual architecture.
|
289 |
+
*
|
290 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
291 |
+
* \param [out] cubin Compiled and assembled result.
|
292 |
+
* \return
|
293 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
294 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
295 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
296 |
+
*
|
297 |
+
* \see ::nvrtcGetCUBINSize
|
298 |
+
*/
|
299 |
+
nvrtcResult nvrtcGetCUBIN(nvrtcProgram prog, char *cubin);
|
300 |
+
|
301 |
+
|
302 |
+
#if defined(_WIN32)
|
303 |
+
# define __DEPRECATED__(msg) __declspec(deprecated(msg))
|
304 |
+
#elif (defined(__GNUC__) && (__GNUC__ < 4 || (__GNUC__ == 4 && __GNUC_MINOR__ < 5 && !defined(__clang__))))
|
305 |
+
# define __DEPRECATED__(msg) __attribute__((deprecated))
|
306 |
+
#elif (defined(__GNUC__))
|
307 |
+
# define __DEPRECATED__(msg) __attribute__((deprecated(msg)))
|
308 |
+
#else
|
309 |
+
# define __DEPRECATED__(msg)
|
310 |
+
#endif
|
311 |
+
|
312 |
+
/**
|
313 |
+
* \ingroup compilation
|
314 |
+
* \brief
|
315 |
+
* DEPRECATION NOTICE: This function will be removed in a future release. Please use
|
316 |
+
* nvrtcGetLTOIRSize (and nvrtcGetLTOIR) instead.
|
317 |
+
*/
|
318 |
+
__DEPRECATED__("This function will be removed in a future release. Please use nvrtcGetLTOIRSize instead")
|
319 |
+
nvrtcResult nvrtcGetNVVMSize(nvrtcProgram prog, size_t *nvvmSizeRet);
|
320 |
+
|
321 |
+
/**
|
322 |
+
* \ingroup compilation
|
323 |
+
* \brief
|
324 |
+
* DEPRECATION NOTICE: This function will be removed in a future release. Please use
|
325 |
+
* nvrtcGetLTOIR (and nvrtcGetLTOIRSize) instead.
|
326 |
+
*/
|
327 |
+
__DEPRECATED__("This function will be removed in a future release. Please use nvrtcGetLTOIR instead")
|
328 |
+
nvrtcResult nvrtcGetNVVM(nvrtcProgram prog, char *nvvm);
|
329 |
+
|
330 |
+
#undef __DEPRECATED__
|
331 |
+
|
332 |
+
/**
|
333 |
+
* \ingroup compilation
|
334 |
+
* \brief nvrtcGetLTOIRSize sets the value of \p LTOIRSizeRet with the size of the LTO IR
|
335 |
+
* generated by the previous compilation of \p prog. The value of
|
336 |
+
* LTOIRSizeRet is set to 0 if the program was not compiled with
|
337 |
+
* \c -dlto.
|
338 |
+
*
|
339 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
340 |
+
* \param [out] LTOIRSizeRet Size of the generated LTO IR.
|
341 |
+
* \return
|
342 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
343 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
344 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
345 |
+
*
|
346 |
+
* \see ::nvrtcGetLTOIR
|
347 |
+
*/
|
348 |
+
nvrtcResult nvrtcGetLTOIRSize(nvrtcProgram prog, size_t *LTOIRSizeRet);
|
349 |
+
|
350 |
+
|
351 |
+
/**
|
352 |
+
* \ingroup compilation
|
353 |
+
* \brief nvrtcGetLTOIR stores the LTO IR generated by the previous compilation
|
354 |
+
* of \p prog in the memory pointed by \p LTOIR. No LTO IR is available
|
355 |
+
* if the program was compiled without \c -dlto.
|
356 |
+
*
|
357 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
358 |
+
* \param [out] LTOIR Compiled result.
|
359 |
+
* \return
|
360 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
361 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
362 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
363 |
+
*
|
364 |
+
* \see ::nvrtcGetLTOIRSize
|
365 |
+
*/
|
366 |
+
nvrtcResult nvrtcGetLTOIR(nvrtcProgram prog, char *LTOIR);
|
367 |
+
|
368 |
+
|
369 |
+
/**
|
370 |
+
* \ingroup compilation
|
371 |
+
* \brief nvrtcGetOptiXIRSize sets the value of \p optixirSizeRet with the size of the OptiX IR
|
372 |
+
* generated by the previous compilation of \p prog. The value of
|
373 |
+
* nvrtcGetOptiXIRSize is set to 0 if the program was compiled with
|
374 |
+
* options incompatible with OptiX IR generation.
|
375 |
+
*
|
376 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
377 |
+
* \param [out] optixirSizeRet Size of the generated LTO IR.
|
378 |
+
* \return
|
379 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
380 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
381 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
382 |
+
*
|
383 |
+
* \see ::nvrtcGetOptiXIR
|
384 |
+
*/
|
385 |
+
nvrtcResult nvrtcGetOptiXIRSize(nvrtcProgram prog, size_t *optixirSizeRet);
|
386 |
+
|
387 |
+
|
388 |
+
/**
|
389 |
+
* \ingroup compilation
|
390 |
+
* \brief nvrtcGetOptiXIR stores the OptiX IR generated by the previous compilation
|
391 |
+
* of \p prog in the memory pointed by \p optixir. No OptiX IR is available
|
392 |
+
* if the program was compiled with options incompatible with OptiX IR generation.
|
393 |
+
*
|
394 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
395 |
+
* \param [out] Optix IR Compiled result.
|
396 |
+
* \return
|
397 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
398 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
399 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
400 |
+
*
|
401 |
+
* \see ::nvrtcGetOptiXIRSize
|
402 |
+
*/
|
403 |
+
nvrtcResult nvrtcGetOptiXIR(nvrtcProgram prog, char *optixir);
|
404 |
+
|
405 |
+
/**
|
406 |
+
* \ingroup compilation
|
407 |
+
* \brief nvrtcGetProgramLogSize sets \p logSizeRet with the size of the
|
408 |
+
* log generated by the previous compilation of \p prog (including the
|
409 |
+
* trailing \c NULL).
|
410 |
+
*
|
411 |
+
* Note that compilation log may be generated with warnings and informative
|
412 |
+
* messages, even when the compilation of \p prog succeeds.
|
413 |
+
*
|
414 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
415 |
+
* \param [out] logSizeRet Size of the compilation log
|
416 |
+
* (including the trailing \c NULL).
|
417 |
+
* \return
|
418 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
419 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
420 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
421 |
+
*
|
422 |
+
* \see ::nvrtcGetProgramLog
|
423 |
+
*/
|
424 |
+
nvrtcResult nvrtcGetProgramLogSize(nvrtcProgram prog, size_t *logSizeRet);
|
425 |
+
|
426 |
+
|
427 |
+
/**
|
428 |
+
* \ingroup compilation
|
429 |
+
* \brief nvrtcGetProgramLog stores the log generated by the previous
|
430 |
+
* compilation of \p prog in the memory pointed by \p log.
|
431 |
+
*
|
432 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
433 |
+
* \param [out] log Compilation log.
|
434 |
+
* \return
|
435 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
436 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_INPUT \endlink
|
437 |
+
* - \link #nvrtcResult NVRTC_ERROR_INVALID_PROGRAM \endlink
|
438 |
+
*
|
439 |
+
* \see ::nvrtcGetProgramLogSize
|
440 |
+
*/
|
441 |
+
nvrtcResult nvrtcGetProgramLog(nvrtcProgram prog, char *log);
|
442 |
+
|
443 |
+
|
444 |
+
/**
|
445 |
+
* \ingroup compilation
|
446 |
+
* \brief nvrtcAddNameExpression notes the given name expression
|
447 |
+
* denoting the address of a __global__ function
|
448 |
+
* or __device__/__constant__ variable.
|
449 |
+
*
|
450 |
+
* The identical name expression string must be provided on a subsequent
|
451 |
+
* call to nvrtcGetLoweredName to extract the lowered name.
|
452 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
453 |
+
* \param [in] name_expression constant expression denoting the address of
|
454 |
+
* a __global__ function or __device__/__constant__ variable.
|
455 |
+
* \return
|
456 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
457 |
+
* - \link #nvrtcResult NVRTC_ERROR_NO_NAME_EXPRESSIONS_AFTER_COMPILATION \endlink
|
458 |
+
*
|
459 |
+
* \see ::nvrtcGetLoweredName
|
460 |
+
*/
|
461 |
+
nvrtcResult nvrtcAddNameExpression(nvrtcProgram prog,
|
462 |
+
const char * const name_expression);
|
463 |
+
|
464 |
+
/**
|
465 |
+
* \ingroup compilation
|
466 |
+
* \brief nvrtcGetLoweredName extracts the lowered (mangled) name
|
467 |
+
* for a __global__ function or __device__/__constant__ variable,
|
468 |
+
* and updates *lowered_name to point to it. The memory containing
|
469 |
+
* the name is released when the NVRTC program is destroyed by
|
470 |
+
* nvrtcDestroyProgram.
|
471 |
+
* The identical name expression must have been previously
|
472 |
+
* provided to nvrtcAddNameExpression.
|
473 |
+
*
|
474 |
+
* \param [in] prog CUDA Runtime Compilation program.
|
475 |
+
* \param [in] name_expression constant expression denoting the address of
|
476 |
+
* a __global__ function or __device__/__constant__ variable.
|
477 |
+
* \param [out] lowered_name initialized by the function to point to a
|
478 |
+
* C string containing the lowered (mangled)
|
479 |
+
* name corresponding to the provided name expression.
|
480 |
+
* \return
|
481 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
482 |
+
* - \link #nvrtcResult NVRTC_ERROR_NO_LOWERED_NAMES_BEFORE_COMPILATION \endlink
|
483 |
+
* - \link #nvrtcResult NVRTC_ERROR_NAME_EXPRESSION_NOT_VALID \endlink
|
484 |
+
*
|
485 |
+
* \see ::nvrtcAddNameExpression
|
486 |
+
*/
|
487 |
+
nvrtcResult nvrtcGetLoweredName(nvrtcProgram prog,
|
488 |
+
const char *const name_expression,
|
489 |
+
const char** lowered_name);
|
490 |
+
|
491 |
+
|
492 |
+
/**
|
493 |
+
* \defgroup options Supported Compile Options
|
494 |
+
*
|
495 |
+
* NVRTC supports the compile options below.
|
496 |
+
* Option names with two preceding dashs (\c --) are long option names and
|
497 |
+
* option names with one preceding dash (\c -) are short option names.
|
498 |
+
* Short option names can be used instead of long option names.
|
499 |
+
* When a compile option takes an argument, an assignment operator (\c =)
|
500 |
+
* is used to separate the compile option argument from the compile option
|
501 |
+
* name, e.g., \c "--gpu-architecture=compute_60".
|
502 |
+
* Alternatively, the compile option name and the argument can be specified in
|
503 |
+
* separate strings without an assignment operator, .e.g,
|
504 |
+
* \c "--gpu-architecture" \c "compute_60".
|
505 |
+
* Single-character short option names, such as \c -D, \c -U, and \c -I, do
|
506 |
+
* not require an assignment operator, and the compile option name and the
|
507 |
+
* argument can be present in the same string with or without spaces between
|
508 |
+
* them.
|
509 |
+
* For instance, \c "-D=<def>", \c "-D<def>", and \c "-D <def>" are all
|
510 |
+
* supported.
|
511 |
+
*
|
512 |
+
* The valid compiler options are:
|
513 |
+
*
|
514 |
+
* - Compilation targets
|
515 |
+
* - \c --gpu-architecture=\<arch\> (\c -arch)\n
|
516 |
+
* Specify the name of the class of GPU architectures for which the
|
517 |
+
* input must be compiled.\n
|
518 |
+
* - Valid <c>\<arch\></c>s:
|
519 |
+
* - \c compute_50
|
520 |
+
* - \c compute_52
|
521 |
+
* - \c compute_53
|
522 |
+
* - \c compute_60
|
523 |
+
* - \c compute_61
|
524 |
+
* - \c compute_62
|
525 |
+
* - \c compute_70
|
526 |
+
* - \c compute_72
|
527 |
+
* - \c compute_75
|
528 |
+
* - \c compute_80
|
529 |
+
* - \c compute_87
|
530 |
+
* - \c compute_89
|
531 |
+
* - \c compute_90
|
532 |
+
* - \c compute_90a
|
533 |
+
* - \c sm_50
|
534 |
+
* - \c sm_52
|
535 |
+
* - \c sm_53
|
536 |
+
* - \c sm_60
|
537 |
+
* - \c sm_61
|
538 |
+
* - \c sm_62
|
539 |
+
* - \c sm_70
|
540 |
+
* - \c sm_72
|
541 |
+
* - \c sm_75
|
542 |
+
* - \c sm_80
|
543 |
+
* - \c sm_87
|
544 |
+
* - \c sm_89
|
545 |
+
* - \c sm_90
|
546 |
+
* - \c sm_90a
|
547 |
+
* - Default: \c compute_52
|
548 |
+
* - Separate compilation / whole-program compilation
|
549 |
+
* - \c --device-c (\c -dc)\n
|
550 |
+
* Generate relocatable code that can be linked with other relocatable
|
551 |
+
* device code. It is equivalent to --relocatable-device-code=true.
|
552 |
+
* - \c --device-w (\c -dw)\n
|
553 |
+
* Generate non-relocatable code. It is equivalent to
|
554 |
+
* \c --relocatable-device-code=false.
|
555 |
+
* - \c --relocatable-device-code={true|false} (\c -rdc)\n
|
556 |
+
* Enable (disable) the generation of relocatable device code.
|
557 |
+
* - Default: \c false
|
558 |
+
* - \c --extensible-whole-program (\c -ewp)\n
|
559 |
+
* Do extensible whole program compilation of device code.
|
560 |
+
* - Default: \c false
|
561 |
+
* - Debugging support
|
562 |
+
* - \c --device-debug (\c -G)\n
|
563 |
+
* Generate debug information. If --dopt is not specified,
|
564 |
+
* then turns off all optimizations.
|
565 |
+
* - \c --generate-line-info (\c -lineinfo)\n
|
566 |
+
* Generate line-number information.
|
567 |
+
* - Code generation
|
568 |
+
* - \c --dopt on (\c -dopt)\n
|
569 |
+
* - \c --dopt=on \n
|
570 |
+
* Enable device code optimization. When specified along with '-G', enables
|
571 |
+
* limited debug information generation for optimized device code (currently,
|
572 |
+
* only line number information).
|
573 |
+
* When '-G' is not specified, '-dopt=on' is implicit.
|
574 |
+
* - \c --ptxas-options \<options\> (\c -Xptxas)\n
|
575 |
+
* - \c --ptxas-options=\<options\> \n
|
576 |
+
* Specify options directly to ptxas, the PTX optimizing assembler.
|
577 |
+
* - \c --maxrregcount=\<N\> (\c -maxrregcount)\n
|
578 |
+
* Specify the maximum amount of registers that GPU functions can use.
|
579 |
+
* Until a function-specific limit, a higher value will generally
|
580 |
+
* increase the performance of individual GPU threads that execute this
|
581 |
+
* function. However, because thread registers are allocated from a
|
582 |
+
* global register pool on each GPU, a higher value of this option will
|
583 |
+
* also reduce the maximum thread block size, thereby reducing the amount
|
584 |
+
* of thread parallelism. Hence, a good maxrregcount value is the result
|
585 |
+
* of a trade-off. If this option is not specified, then no maximum is
|
586 |
+
* assumed. Value less than the minimum registers required by ABI will
|
587 |
+
* be bumped up by the compiler to ABI minimum limit.
|
588 |
+
* - \c --ftz={true|false} (\c -ftz)\n
|
589 |
+
* When performing single-precision floating-point operations, flush
|
590 |
+
* denormal values to zero or preserve denormal values.
|
591 |
+
* \c --use_fast_math implies \c --ftz=true.
|
592 |
+
* - Default: \c false
|
593 |
+
* - \c --prec-sqrt={true|false} (\c -prec-sqrt)\n
|
594 |
+
* For single-precision floating-point square root, use IEEE
|
595 |
+
* round-to-nearest mode or use a faster approximation.
|
596 |
+
* \c --use_fast_math implies \c --prec-sqrt=false.
|
597 |
+
* - Default: \c true
|
598 |
+
* - \c --prec-div={true|false} (\c -prec-div)\n
|
599 |
+
* For single-precision floating-point division and reciprocals, use IEEE
|
600 |
+
* round-to-nearest mode or use a faster approximation.
|
601 |
+
* \c --use_fast_math implies \c --prec-div=false.
|
602 |
+
* - Default: \c true
|
603 |
+
* - \c --fmad={true|false} (\c -fmad)\n
|
604 |
+
* Enables (disables) the contraction of floating-point multiplies and
|
605 |
+
* adds/subtracts into floating-point multiply-add operations (FMAD,
|
606 |
+
* FFMA, or DFMA). \c --use_fast_math implies \c --fmad=true.
|
607 |
+
* - Default: \c true
|
608 |
+
* - \c --use_fast_math (\c -use_fast_math)\n
|
609 |
+
* Make use of fast math operations.
|
610 |
+
* \c --use_fast_math implies \c --ftz=true \c --prec-div=false
|
611 |
+
* \c --prec-sqrt=false \c --fmad=true.
|
612 |
+
* - \c --extra-device-vectorization (\c -extra-device-vectorization)\n
|
613 |
+
* Enables more aggressive device code vectorization in the NVVM optimizer.
|
614 |
+
* - \c --modify-stack-limit={true|false} (\c -modify-stack-limit)\n
|
615 |
+
* On Linux, during compilation, use \c setrlimit() to increase stack size
|
616 |
+
* to maximum allowed. The limit is reset to the previous value at the
|
617 |
+
* end of compilation.
|
618 |
+
* Note: \c setrlimit() changes the value for the entire process.
|
619 |
+
* - Default: \c true
|
620 |
+
* - \c --dlink-time-opt (\c -dlto)\n
|
621 |
+
* Generate intermediate code for later link-time optimization.
|
622 |
+
* It implies \c -rdc=true.
|
623 |
+
* Note: when this option is used the nvrtcGetLTOIR API should be used,
|
624 |
+
* as PTX or Cubin will not be generated.
|
625 |
+
* - \c --gen-opt-lto (\c -gen-opt-lto)\n
|
626 |
+
* Run the optimizer passes before generating the LTO IR.
|
627 |
+
* - \c --optix-ir (\c -optix-ir)\n
|
628 |
+
* Generate OptiX IR. The Optix IR is only intended for consumption by OptiX
|
629 |
+
* through appropriate APIs. This feature is not supported with
|
630 |
+
* link-time-optimization (\c -dlto)\n.
|
631 |
+
* Note: when this option is used the nvrtcGetOptiX API should be used,
|
632 |
+
* as PTX or Cubin will not be generated.
|
633 |
+
* - Preprocessing
|
634 |
+
* - \c --define-macro=\<def\> (\c -D)\n
|
635 |
+
* \c \<def\> can be either \c \<name\> or \c \<name=definitions\>.
|
636 |
+
* - \c \<name\> \n
|
637 |
+
* Predefine \c \<name\> as a macro with definition \c 1.
|
638 |
+
* - \c \<name\>=\<definition\> \n
|
639 |
+
* The contents of \c \<definition\> are tokenized and preprocessed
|
640 |
+
* as if they appeared during translation phase three in a \c \#define
|
641 |
+
* directive. In particular, the definition will be truncated by
|
642 |
+
* embedded new line characters.
|
643 |
+
* - \c --undefine-macro=\<def\> (\c -U)\n
|
644 |
+
* Cancel any previous definition of \c \<def\>.
|
645 |
+
* - \c --include-path=\<dir\> (\c -I)\n
|
646 |
+
* Add the directory \c \<dir\> to the list of directories to be
|
647 |
+
* searched for headers. These paths are searched after the list of
|
648 |
+
* headers given to ::nvrtcCreateProgram.
|
649 |
+
* - \c --pre-include=\<header\> (\c -include)\n
|
650 |
+
* Preinclude \c \<header\> during preprocessing.
|
651 |
+
* - \c --no-source-include (\c -no-source-include)
|
652 |
+
* The preprocessor by default adds the directory of each input sources
|
653 |
+
* to the include path. This option disables this feature and only
|
654 |
+
* considers the path specified explicitly.
|
655 |
+
* - Language Dialect
|
656 |
+
* - \c --std={c++03|c++11|c++14|c++17|c++20}
|
657 |
+
* (\c -std={c++11|c++14|c++17|c++20})\n
|
658 |
+
* Set language dialect to C++03, C++11, C++14, C++17 or C++20
|
659 |
+
* - Default: \c c++17
|
660 |
+
* - \c --builtin-move-forward={true|false} (\c -builtin-move-forward)\n
|
661 |
+
* Provide builtin definitions of \c std::move and \c std::forward,
|
662 |
+
* when C++11 or later language dialect is selected.
|
663 |
+
* - Default: \c true
|
664 |
+
* - \c --builtin-initializer-list={true|false}
|
665 |
+
* (\c -builtin-initializer-list)\n
|
666 |
+
* Provide builtin definitions of \c std::initializer_list class and
|
667 |
+
* member functions when C++11 or later language dialect is selected.
|
668 |
+
* - Default: \c true
|
669 |
+
* - Misc.
|
670 |
+
* - \c --disable-warnings (\c -w)\n
|
671 |
+
* Inhibit all warning messages.
|
672 |
+
* - \c --restrict (\c -restrict)\n
|
673 |
+
* Programmer assertion that all kernel pointer parameters are restrict
|
674 |
+
* pointers.
|
675 |
+
* - \c --device-as-default-execution-space
|
676 |
+
* (\c -default-device)\n
|
677 |
+
* Treat entities with no execution space annotation as \c __device__
|
678 |
+
* entities.
|
679 |
+
* - \c --device-int128 (\c -device-int128)\n
|
680 |
+
* Allow the \c __int128 type in device code. Also causes the macro \c __CUDACC_RTC_INT128__
|
681 |
+
* to be defined.
|
682 |
+
* - \c --optimization-info=\<kind\> (\c -opt-info)\n
|
683 |
+
* Provide optimization reports for the specified kind of optimization.
|
684 |
+
* The following kind tags are supported:
|
685 |
+
* - \c inline : emit a remark when a function is inlined.
|
686 |
+
* - \c --version-ident={true|false} (\c -dQ)\n
|
687 |
+
* Embed used compiler's version info into generated PTX/CUBIN
|
688 |
+
* - Default: \c false
|
689 |
+
* - \c --display-error-number (\c -err-no)\n
|
690 |
+
* Display diagnostic number for warning messages. (Default)
|
691 |
+
* - \c --no-display-error-number (\c -no-err-no)\n
|
692 |
+
* Disables the display of a diagnostic number for warning messages.
|
693 |
+
* - \c --diag-error=<error-number>,... (\c -diag-error)\n
|
694 |
+
* Emit error for specified diagnostic message number(s). Message numbers can be separated by comma.
|
695 |
+
* - \c --diag-suppress=<error-number>,... (\c -diag-suppress)\n
|
696 |
+
* Suppress specified diagnostic message number(s). Message numbers can be separated by comma.
|
697 |
+
* - \c --diag-warn=<error-number>,... (\c -diag-warn)\n
|
698 |
+
* Emit warning for specified diagnostic message number(s). Message numbers can be separated by comma.
|
699 |
+
* - \c --brief-diagnostics={true|false} (\c -brief-diag)\n
|
700 |
+
* This option disables or enables showing source line and column info
|
701 |
+
* in a diagnostic.
|
702 |
+
* The --brief-diagnostics=true will not show the source line and column info.
|
703 |
+
* - Default: \c false
|
704 |
+
* - \c --time=<file-name> (\c -time)\n
|
705 |
+
* Generate a comma separated value table with the time taken by each compilation
|
706 |
+
* phase, and append it at the end of the file given as the option argument.
|
707 |
+
* If the file does not exist, the column headings are generated in the first row
|
708 |
+
* of the table. If the file name is '-', the timing data is written to the compilation log.
|
709 |
+
*
|
710 |
+
*/
|
711 |
+
|
712 |
+
|
713 |
+
#ifdef __cplusplus
|
714 |
+
}
|
715 |
+
#endif /* __cplusplus */
|
716 |
+
|
717 |
+
|
718 |
+
/* The utility function 'nvrtcGetTypeName' is not available by default. Define
|
719 |
+
the macro 'NVRTC_GET_TYPE_NAME' to a non-zero value to make it available.
|
720 |
+
*/
|
721 |
+
|
722 |
+
#if NVRTC_GET_TYPE_NAME || __DOXYGEN_ONLY__
|
723 |
+
|
724 |
+
#if NVRTC_USE_CXXABI || __clang__ || __GNUC__ || __DOXYGEN_ONLY__
|
725 |
+
#include <cxxabi.h>
|
726 |
+
#include <cstdlib>
|
727 |
+
|
728 |
+
#elif defined(_WIN32)
|
729 |
+
#include <Windows.h>
|
730 |
+
#include <DbgHelp.h>
|
731 |
+
#endif /* NVRTC_USE_CXXABI || __clang__ || __GNUC__ */
|
732 |
+
|
733 |
+
|
734 |
+
#include <string>
|
735 |
+
#include <typeinfo>
|
736 |
+
|
737 |
+
template <typename T> struct __nvrtcGetTypeName_helper_t { };
|
738 |
+
|
739 |
+
/*************************************************************************//**
|
740 |
+
*
|
741 |
+
* \defgroup hosthelper Host Helper
|
742 |
+
*
|
743 |
+
* NVRTC defines the following functions for easier interaction with host code.
|
744 |
+
*
|
745 |
+
****************************************************************************/
|
746 |
+
|
747 |
+
/**
|
748 |
+
* \ingroup hosthelper
|
749 |
+
* \brief nvrtcGetTypeName stores the source level name of a type in the given
|
750 |
+
* std::string location.
|
751 |
+
*
|
752 |
+
* This function is only provided when the macro NVRTC_GET_TYPE_NAME is
|
753 |
+
* defined with a non-zero value. It uses abi::__cxa_demangle or UnDecorateSymbolName
|
754 |
+
* function calls to extract the type name, when using gcc/clang or cl.exe compilers,
|
755 |
+
* respectively. If the name extraction fails, it will return NVRTC_INTERNAL_ERROR,
|
756 |
+
* otherwise *result is initialized with the extracted name.
|
757 |
+
*
|
758 |
+
* Windows-specific notes:
|
759 |
+
* - nvrtcGetTypeName() is not multi-thread safe because it calls UnDecorateSymbolName(),
|
760 |
+
* which is not multi-thread safe.
|
761 |
+
* - The returned string may contain Microsoft-specific keywords such as __ptr64 and __cdecl.
|
762 |
+
*
|
763 |
+
* \param [in] tinfo: reference to object of type std::type_info for a given type.
|
764 |
+
* \param [in] result: pointer to std::string in which to store the type name.
|
765 |
+
* \return
|
766 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
767 |
+
* - \link #nvrtcResult NVRTC_ERROR_INTERNAL_ERROR \endlink
|
768 |
+
*
|
769 |
+
*/
|
770 |
+
inline nvrtcResult nvrtcGetTypeName(const std::type_info &tinfo, std::string *result)
|
771 |
+
{
|
772 |
+
#if USE_CXXABI || __clang__ || __GNUC__
|
773 |
+
const char *name = tinfo.name();
|
774 |
+
int status;
|
775 |
+
char *undecorated_name = abi::__cxa_demangle(name, 0, 0, &status);
|
776 |
+
if (status == 0) {
|
777 |
+
*result = undecorated_name;
|
778 |
+
free(undecorated_name);
|
779 |
+
return NVRTC_SUCCESS;
|
780 |
+
}
|
781 |
+
#elif defined(_WIN32)
|
782 |
+
const char *name = tinfo.raw_name();
|
783 |
+
if (!name || *name != '.') {
|
784 |
+
return NVRTC_ERROR_INTERNAL_ERROR;
|
785 |
+
}
|
786 |
+
char undecorated_name[4096];
|
787 |
+
//name+1 skips over the '.' prefix
|
788 |
+
if(UnDecorateSymbolName(name+1, undecorated_name,
|
789 |
+
sizeof(undecorated_name) / sizeof(*undecorated_name),
|
790 |
+
//note: doesn't seem to work correctly without UNDNAME_NO_ARGUMENTS.
|
791 |
+
UNDNAME_NO_ARGUMENTS | UNDNAME_NAME_ONLY ) ) {
|
792 |
+
*result = undecorated_name;
|
793 |
+
return NVRTC_SUCCESS;
|
794 |
+
}
|
795 |
+
#endif /* USE_CXXABI || __clang__ || __GNUC__ */
|
796 |
+
|
797 |
+
return NVRTC_ERROR_INTERNAL_ERROR;
|
798 |
+
}
|
799 |
+
|
800 |
+
/**
|
801 |
+
* \ingroup hosthelper
|
802 |
+
* \brief nvrtcGetTypeName stores the source level name of the template type argument
|
803 |
+
* T in the given std::string location.
|
804 |
+
*
|
805 |
+
* This function is only provided when the macro NVRTC_GET_TYPE_NAME is
|
806 |
+
* defined with a non-zero value. It uses abi::__cxa_demangle or UnDecorateSymbolName
|
807 |
+
* function calls to extract the type name, when using gcc/clang or cl.exe compilers,
|
808 |
+
* respectively. If the name extraction fails, it will return NVRTC_INTERNAL_ERROR,
|
809 |
+
* otherwise *result is initialized with the extracted name.
|
810 |
+
*
|
811 |
+
* Windows-specific notes:
|
812 |
+
* - nvrtcGetTypeName() is not multi-thread safe because it calls UnDecorateSymbolName(),
|
813 |
+
* which is not multi-thread safe.
|
814 |
+
* - The returned string may contain Microsoft-specific keywords such as __ptr64 and __cdecl.
|
815 |
+
*
|
816 |
+
* \param [in] result: pointer to std::string in which to store the type name.
|
817 |
+
* \return
|
818 |
+
* - \link #nvrtcResult NVRTC_SUCCESS \endlink
|
819 |
+
* - \link #nvrtcResult NVRTC_ERROR_INTERNAL_ERROR \endlink
|
820 |
+
*
|
821 |
+
*/
|
822 |
+
|
823 |
+
template <typename T>
|
824 |
+
nvrtcResult nvrtcGetTypeName(std::string *result)
|
825 |
+
{
|
826 |
+
nvrtcResult res = nvrtcGetTypeName(typeid(__nvrtcGetTypeName_helper_t<T>),
|
827 |
+
result);
|
828 |
+
if (res != NVRTC_SUCCESS)
|
829 |
+
return res;
|
830 |
+
|
831 |
+
std::string repr = *result;
|
832 |
+
std::size_t idx = repr.find("__nvrtcGetTypeName_helper_t");
|
833 |
+
idx = (idx != std::string::npos) ? repr.find("<", idx) : idx;
|
834 |
+
std::size_t last_idx = repr.find_last_of('>');
|
835 |
+
if (idx == std::string::npos || last_idx == std::string::npos) {
|
836 |
+
return NVRTC_ERROR_INTERNAL_ERROR;
|
837 |
+
}
|
838 |
+
++idx;
|
839 |
+
*result = repr.substr(idx, last_idx - idx);
|
840 |
+
return NVRTC_SUCCESS;
|
841 |
+
}
|
842 |
+
|
843 |
+
#endif /* NVRTC_GET_TYPE_NAME */
|
844 |
+
|
845 |
+
#endif /* __NVRTC_H__ */
|
llmeval-env/lib/python3.10/site-packages/nvidia/cuda_nvrtc/lib/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (194 Bytes). View file
|
|
llmeval-env/lib/python3.10/site-packages/nvidia/curand/__pycache__/__init__.cpython-310.pyc
ADDED
Binary file (186 Bytes). View file
|
|
llmeval-env/lib/python3.10/site-packages/nvidia/curand/include/curand_globals.h
ADDED
@@ -0,0 +1,93 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
/* Copyright 2010-2014 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 |
+
#ifndef CURAND_GLOBALS_H
|
49 |
+
#define CURAND_GLOBALS_H
|
50 |
+
|
51 |
+
#define MAX_XOR_N (5)
|
52 |
+
#define SKIPAHEAD_BLOCKSIZE (4)
|
53 |
+
#define SKIPAHEAD_MASK ((1<<SKIPAHEAD_BLOCKSIZE)-1)
|
54 |
+
#define CURAND_2POW32 (4294967296.f)
|
55 |
+
#define CURAND_2POW32_DOUBLE (4294967296.)
|
56 |
+
#define CURAND_2POW32_INV (2.3283064e-10f)
|
57 |
+
#define CURAND_2POW32_INV_DOUBLE (2.3283064365386963e-10)
|
58 |
+
#define CURAND_2POW53_INV_DOUBLE (1.1102230246251565e-16)
|
59 |
+
#define CURAND_2POW32_INV_2PI (2.3283064e-10f * 6.2831855f)
|
60 |
+
#define CURAND_2PI (6.2831855f)
|
61 |
+
#define CURAND_2POW53_INV_2PI_DOUBLE (1.1102230246251565e-16 * 6.2831853071795860)
|
62 |
+
#define CURAND_PI_DOUBLE (3.1415926535897932)
|
63 |
+
#define CURAND_2PI_DOUBLE (6.2831853071795860)
|
64 |
+
#define CURAND_SQRT2 (-1.4142135f)
|
65 |
+
#define CURAND_SQRT2_DOUBLE (-1.4142135623730951)
|
66 |
+
|
67 |
+
#define SOBOL64_ITR_BINARY_DIVIDE 2
|
68 |
+
#define SOBOL_M2_BINARY_DIVIDE 10
|
69 |
+
#define MTGP32_M2_BINARY_DIVIDE 32
|
70 |
+
#define MAX_LAMBDA 400000
|
71 |
+
#define MIN_GAUSS_LAMBDA 2000
|
72 |
+
|
73 |
+
struct normal_args_st {
|
74 |
+
float mean;
|
75 |
+
float stddev;
|
76 |
+
};
|
77 |
+
|
78 |
+
typedef struct normal_args_st normal_args_t;
|
79 |
+
|
80 |
+
struct normal_args_double_st {
|
81 |
+
double mean;
|
82 |
+
double stddev;
|
83 |
+
};
|
84 |
+
|
85 |
+
typedef struct normal_args_double_st normal_args_double_t;
|
86 |
+
|
87 |
+
|
88 |
+
|
89 |
+
|
90 |
+
|
91 |
+
|
92 |
+
|
93 |
+
#endif
|
llmeval-env/lib/python3.10/site-packages/nvidia/curand/include/curand_lognormal.h
ADDED
@@ -0,0 +1,697 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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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|
|
|
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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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|
|
|
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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 |
+
* The 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 |
+
* The Licensed Deliverables contained herein are PROPRIETARY and
|
11 |
+
* CONFIDENTIAL to NVIDIA and are 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. THEY ARE
|
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 are 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 |
+
#if !defined(CURAND_LOGNORMAL_H_)
|
52 |
+
#define CURAND_LOGNORMAL_H_
|
53 |
+
|
54 |
+
/**
|
55 |
+
* \defgroup DEVICE Device API
|
56 |
+
*
|
57 |
+
* @{
|
58 |
+
*/
|
59 |
+
|
60 |
+
#ifndef __CUDACC_RTC__
|
61 |
+
#include <math.h>
|
62 |
+
#endif // __CUDACC_RTC__
|
63 |
+
|
64 |
+
#include "curand_mrg32k3a.h"
|
65 |
+
#include "curand_mtgp32_kernel.h"
|
66 |
+
#include "curand_philox4x32_x.h"
|
67 |
+
|
68 |
+
/**
|
69 |
+
* \brief Return a log-normally distributed float from an XORWOW generator.
|
70 |
+
*
|
71 |
+
* Return a single log-normally distributed float derived from a normal
|
72 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
73 |
+
* from the XORWOW generator in \p state,
|
74 |
+
* increment position of generator by one.
|
75 |
+
*
|
76 |
+
* The implementation uses a Box-Muller transform to generate two
|
77 |
+
* normally distributed results, transforms them to log-normal distribution,
|
78 |
+
* then returns them one at a time.
|
79 |
+
* See ::curand_log_normal2() for a more efficient version that returns
|
80 |
+
* both results at once.
|
81 |
+
*
|
82 |
+
* \param state - Pointer to state to update
|
83 |
+
* \param mean - Mean of the related normal distribution
|
84 |
+
* \param stddev - Standard deviation of the related normal distribution
|
85 |
+
*
|
86 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
87 |
+
*/
|
88 |
+
QUALIFIERS float curand_log_normal(curandStateXORWOW_t *state, float mean, float stddev)
|
89 |
+
{
|
90 |
+
if(state->boxmuller_flag != EXTRA_FLAG_LOG_NORMAL) {
|
91 |
+
unsigned int x, y;
|
92 |
+
x = curand(state);
|
93 |
+
y = curand(state);
|
94 |
+
float2 v = _curand_box_muller(x, y);
|
95 |
+
state->boxmuller_extra = expf(mean + (stddev * v.y));
|
96 |
+
state->boxmuller_flag = EXTRA_FLAG_LOG_NORMAL;
|
97 |
+
return expf(mean + (stddev * v.x));
|
98 |
+
}
|
99 |
+
state->boxmuller_flag = 0;
|
100 |
+
return state->boxmuller_extra;
|
101 |
+
}
|
102 |
+
|
103 |
+
/**
|
104 |
+
* \brief Return a log-normally distributed float from an Philox4_32_10 generator.
|
105 |
+
*
|
106 |
+
* Return a single log-normally distributed float derived from a normal
|
107 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
108 |
+
* from the Philox4_32_10 generator in \p state,
|
109 |
+
* increment position of generator by one.
|
110 |
+
*
|
111 |
+
* The implementation uses a Box-Muller transform to generate two
|
112 |
+
* normally distributed results, transforms them to log-normal distribution,
|
113 |
+
* then returns them one at a time.
|
114 |
+
* See ::curand_log_normal2() for a more efficient version that returns
|
115 |
+
* both results at once.
|
116 |
+
*
|
117 |
+
* \param state - Pointer to state to update
|
118 |
+
* \param mean - Mean of the related normal distribution
|
119 |
+
* \param stddev - Standard deviation of the related normal distribution
|
120 |
+
*
|
121 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
122 |
+
*/
|
123 |
+
|
124 |
+
QUALIFIERS float curand_log_normal(curandStatePhilox4_32_10_t *state, float mean, float stddev)
|
125 |
+
{
|
126 |
+
if(state->boxmuller_flag != EXTRA_FLAG_LOG_NORMAL) {
|
127 |
+
unsigned int x, y;
|
128 |
+
x = curand(state);
|
129 |
+
y = curand(state);
|
130 |
+
float2 v = _curand_box_muller(x, y);
|
131 |
+
state->boxmuller_extra = expf(mean + (stddev * v.y));
|
132 |
+
state->boxmuller_flag = EXTRA_FLAG_LOG_NORMAL;
|
133 |
+
return expf(mean + (stddev * v.x));
|
134 |
+
}
|
135 |
+
state->boxmuller_flag = 0;
|
136 |
+
return state->boxmuller_extra;
|
137 |
+
}
|
138 |
+
|
139 |
+
/**
|
140 |
+
* \brief Return two normally distributed floats from an XORWOW generator.
|
141 |
+
*
|
142 |
+
* Return two log-normally distributed floats derived from a normal
|
143 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
144 |
+
* from the XORWOW generator in \p state,
|
145 |
+
* increment position of generator by two.
|
146 |
+
*
|
147 |
+
* The implementation uses a Box-Muller transform to generate two
|
148 |
+
* normally distributed results, then transforms them to log-normal.
|
149 |
+
*
|
150 |
+
* \param state - Pointer to state to update
|
151 |
+
* \param mean - Mean of the related normal distribution
|
152 |
+
* \param stddev - Standard deviation of the related normal distribution
|
153 |
+
*
|
154 |
+
* \return Log-normally distributed float2 where each element is from a
|
155 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
156 |
+
*/
|
157 |
+
QUALIFIERS float2 curand_log_normal2(curandStateXORWOW_t *state, float mean, float stddev)
|
158 |
+
{
|
159 |
+
float2 v = curand_box_muller(state);
|
160 |
+
v.x = expf(mean + (stddev * v.x));
|
161 |
+
v.y = expf(mean + (stddev * v.y));
|
162 |
+
return v;
|
163 |
+
}
|
164 |
+
|
165 |
+
/**
|
166 |
+
* \brief Return two normally distributed floats from an Philox4_32_10 generator.
|
167 |
+
*
|
168 |
+
* Return two log-normally distributed floats derived from a normal
|
169 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
170 |
+
* from the Philox4_32_10 generator in \p state,
|
171 |
+
* increment position of generator by two.
|
172 |
+
*
|
173 |
+
* The implementation uses a Box-Muller transform to generate two
|
174 |
+
* normally distributed results, then transforms them to log-normal.
|
175 |
+
*
|
176 |
+
* \param state - Pointer to state to update
|
177 |
+
* \param mean - Mean of the related normal distribution
|
178 |
+
* \param stddev - Standard deviation of the related normal distribution
|
179 |
+
*
|
180 |
+
* \return Log-normally distributed float2 where each element is from a
|
181 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
182 |
+
*/
|
183 |
+
QUALIFIERS float2 curand_log_normal2(curandStatePhilox4_32_10_t *state, float mean, float stddev)
|
184 |
+
{
|
185 |
+
float2 v = curand_box_muller(state);
|
186 |
+
v.x = expf(mean + (stddev * v.x));
|
187 |
+
v.y = expf(mean + (stddev * v.y));
|
188 |
+
return v;
|
189 |
+
}
|
190 |
+
/**
|
191 |
+
* \brief Return four normally distributed floats from an Philox4_32_10 generator.
|
192 |
+
*
|
193 |
+
* Return four log-normally distributed floats derived from a normal
|
194 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
195 |
+
* from the Philox4_32_10 generator in \p state,
|
196 |
+
* increment position of generator by four.
|
197 |
+
*
|
198 |
+
* The implementation uses a Box-Muller transform to generate two
|
199 |
+
* normally distributed results, then transforms them to log-normal.
|
200 |
+
*
|
201 |
+
* \param state - Pointer to state to update
|
202 |
+
* \param mean - Mean of the related normal distribution
|
203 |
+
* \param stddev - Standard deviation of the related normal distribution
|
204 |
+
*
|
205 |
+
* \return Log-normally distributed float4 where each element is from a
|
206 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
207 |
+
*/
|
208 |
+
QUALIFIERS float4 curand_log_normal4(curandStatePhilox4_32_10_t *state, float mean, float stddev)
|
209 |
+
{
|
210 |
+
float4 v = curand_box_muller4(state);
|
211 |
+
v.x = expf(mean + (stddev * v.x));
|
212 |
+
v.y = expf(mean + (stddev * v.y));
|
213 |
+
v.z = expf(mean + (stddev * v.z));
|
214 |
+
v.w = expf(mean + (stddev * v.w));
|
215 |
+
return v;
|
216 |
+
}
|
217 |
+
|
218 |
+
/**
|
219 |
+
* \brief Return a log-normally distributed float from an MRG32k3a generator.
|
220 |
+
*
|
221 |
+
* Return a single log-normally distributed float derived from a normal
|
222 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
223 |
+
* from the MRG32k3a generator in \p state,
|
224 |
+
* increment position of generator by one.
|
225 |
+
*
|
226 |
+
* The implementation uses a Box-Muller transform to generate two
|
227 |
+
* normally distributed results, transforms them to log-normal distribution,
|
228 |
+
* then returns them one at a time.
|
229 |
+
* See ::curand_log_normal2() for a more efficient version that returns
|
230 |
+
* both results at once.
|
231 |
+
*
|
232 |
+
* \param state - Pointer to state to update
|
233 |
+
* \param mean - Mean of the related normal distribution
|
234 |
+
* \param stddev - Standard deviation of the related normal distribution
|
235 |
+
*
|
236 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
237 |
+
*/
|
238 |
+
QUALIFIERS float curand_log_normal(curandStateMRG32k3a_t *state, float mean, float stddev)
|
239 |
+
{
|
240 |
+
if(state->boxmuller_flag != EXTRA_FLAG_LOG_NORMAL) {
|
241 |
+
float2 v = curand_box_muller_mrg(state);
|
242 |
+
state->boxmuller_extra = expf(mean + (stddev * v.y));
|
243 |
+
state->boxmuller_flag = EXTRA_FLAG_LOG_NORMAL;
|
244 |
+
return expf(mean + (stddev * v.x));
|
245 |
+
}
|
246 |
+
state->boxmuller_flag = 0;
|
247 |
+
return state->boxmuller_extra;
|
248 |
+
}
|
249 |
+
|
250 |
+
/**
|
251 |
+
* \brief Return two normally distributed floats from an MRG32k3a generator.
|
252 |
+
*
|
253 |
+
* Return two log-normally distributed floats derived from a normal
|
254 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
255 |
+
* from the MRG32k3a generator in \p state,
|
256 |
+
* increment position of generator by two.
|
257 |
+
*
|
258 |
+
* The implementation uses a Box-Muller transform to generate two
|
259 |
+
* normally distributed results, then transforms them to log-normal.
|
260 |
+
*
|
261 |
+
* \param state - Pointer to state to update
|
262 |
+
* \param mean - Mean of the related normal distribution
|
263 |
+
* \param stddev - Standard deviation of the related normal distribution
|
264 |
+
*
|
265 |
+
* \return Log-normally distributed float2 where each element is from a
|
266 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
267 |
+
*/
|
268 |
+
QUALIFIERS float2 curand_log_normal2(curandStateMRG32k3a_t *state, float mean, float stddev)
|
269 |
+
{
|
270 |
+
float2 v = curand_box_muller_mrg(state);
|
271 |
+
v.x = expf(mean + (stddev * v.x));
|
272 |
+
v.y = expf(mean + (stddev * v.y));
|
273 |
+
return v;
|
274 |
+
}
|
275 |
+
|
276 |
+
/**
|
277 |
+
* \brief Return a log-normally distributed float from an MTGP32 generator.
|
278 |
+
*
|
279 |
+
* Return a single log-normally distributed float derived from a normal
|
280 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
281 |
+
* from the MTGP32 generator in \p state,
|
282 |
+
* increment position of generator.
|
283 |
+
*
|
284 |
+
* The implementation uses the inverse cumulative distribution function
|
285 |
+
* to generate a normally distributed result, then transforms the result
|
286 |
+
* to log-normal.
|
287 |
+
*
|
288 |
+
* \param state - Pointer to state to update
|
289 |
+
* \param mean - Mean of the related normal distribution
|
290 |
+
* \param stddev - Standard deviation of the related normal distribution
|
291 |
+
*
|
292 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
293 |
+
*/
|
294 |
+
QUALIFIERS float curand_log_normal(curandStateMtgp32_t *state, float mean, float stddev)
|
295 |
+
{
|
296 |
+
return expf(mean + (stddev * _curand_normal_icdf(curand(state))));
|
297 |
+
}
|
298 |
+
|
299 |
+
/**
|
300 |
+
* \brief Return a log-normally distributed float from a Sobol32 generator.
|
301 |
+
*
|
302 |
+
* Return a single log-normally distributed float derived from a normal
|
303 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
304 |
+
* from the Sobol32 generator in \p state,
|
305 |
+
* increment position of generator by one.
|
306 |
+
*
|
307 |
+
* The implementation uses the inverse cumulative distribution function
|
308 |
+
* to generate a normally distributed result, then transforms the result
|
309 |
+
* to log-normal.
|
310 |
+
*
|
311 |
+
* \param state - Pointer to state to update
|
312 |
+
* \param mean - Mean of the related normal distribution
|
313 |
+
* \param stddev - Standard deviation of the related normal distribution
|
314 |
+
*
|
315 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
316 |
+
*/
|
317 |
+
QUALIFIERS float curand_log_normal(curandStateSobol32_t *state, float mean, float stddev)
|
318 |
+
{
|
319 |
+
return expf(mean + (stddev * _curand_normal_icdf(curand(state))));
|
320 |
+
}
|
321 |
+
/**
|
322 |
+
* \brief Return a log-normally distributed float from a scrambled Sobol32 generator.
|
323 |
+
*
|
324 |
+
* Return a single log-normally distributed float derived from a normal
|
325 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
326 |
+
* from the scrambled Sobol32 generator in \p state,
|
327 |
+
* increment position of generator by one.
|
328 |
+
*
|
329 |
+
* The implementation uses the inverse cumulative distribution function
|
330 |
+
* to generate a normally distributed result, then transforms the result
|
331 |
+
* to log-normal.
|
332 |
+
*
|
333 |
+
* \param state - Pointer to state to update
|
334 |
+
* \param mean - Mean of the related normal distribution
|
335 |
+
* \param stddev - Standard deviation of the related normal distribution
|
336 |
+
*
|
337 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
338 |
+
*/
|
339 |
+
QUALIFIERS float curand_log_normal(curandStateScrambledSobol32_t *state, float mean, float stddev)
|
340 |
+
{
|
341 |
+
return expf(mean + (stddev * _curand_normal_icdf(curand(state))));
|
342 |
+
}
|
343 |
+
|
344 |
+
/**
|
345 |
+
* \brief Return a log-normally distributed float from a Sobol64 generator.
|
346 |
+
*
|
347 |
+
* Return a single log-normally distributed float derived from a normal
|
348 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
349 |
+
* from the Sobol64 generator in \p state,
|
350 |
+
* increment position of generator by one.
|
351 |
+
*
|
352 |
+
* The implementation uses the inverse cumulative distribution function
|
353 |
+
* to generate normally distributed results, then converts to log-normal
|
354 |
+
* distribution.
|
355 |
+
*
|
356 |
+
* \param state - Pointer to state to update
|
357 |
+
* \param mean - Mean of the related normal distribution
|
358 |
+
* \param stddev - Standard deviation of the related normal distribution
|
359 |
+
*
|
360 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
361 |
+
*/
|
362 |
+
QUALIFIERS float curand_log_normal(curandStateSobol64_t *state, float mean, float stddev)
|
363 |
+
{
|
364 |
+
return expf(mean + (stddev * _curand_normal_icdf(curand(state))));
|
365 |
+
}
|
366 |
+
|
367 |
+
/**
|
368 |
+
* \brief Return a log-normally distributed float from a scrambled Sobol64 generator.
|
369 |
+
*
|
370 |
+
* Return a single log-normally distributed float derived from a normal
|
371 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
372 |
+
* from the scrambled Sobol64 generator in \p state,
|
373 |
+
* increment position of generator by one.
|
374 |
+
*
|
375 |
+
* The implementation uses the inverse cumulative distribution function
|
376 |
+
* to generate normally distributed results, then converts to log-normal
|
377 |
+
* distribution.
|
378 |
+
*
|
379 |
+
* \param state - Pointer to state to update
|
380 |
+
* \param mean - Mean of the related normal distribution
|
381 |
+
* \param stddev - Standard deviation of the related normal distribution
|
382 |
+
*
|
383 |
+
* \return Log-normally distributed float with mean \p mean and standard deviation \p stddev
|
384 |
+
*/
|
385 |
+
QUALIFIERS float curand_log_normal(curandStateScrambledSobol64_t *state, float mean, float stddev)
|
386 |
+
{
|
387 |
+
return expf(mean + (stddev * _curand_normal_icdf(curand(state))));
|
388 |
+
}
|
389 |
+
|
390 |
+
/**
|
391 |
+
* \brief Return a log-normally distributed double from an XORWOW generator.
|
392 |
+
*
|
393 |
+
* Return a single normally distributed double derived from a normal
|
394 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
395 |
+
* from the XORWOW generator in \p state,
|
396 |
+
* increment position of generator.
|
397 |
+
*
|
398 |
+
* The implementation uses a Box-Muller transform to generate two
|
399 |
+
* normally distributed results, transforms them to log-normal distribution,
|
400 |
+
* then returns them one at a time.
|
401 |
+
* See ::curand_log_normal2_double() for a more efficient version that returns
|
402 |
+
* both results at once.
|
403 |
+
*
|
404 |
+
* \param state - Pointer to state to update
|
405 |
+
* \param mean - Mean of the related normal distribution
|
406 |
+
* \param stddev - Standard deviation of the related normal distribution
|
407 |
+
*
|
408 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
409 |
+
*/
|
410 |
+
|
411 |
+
QUALIFIERS double curand_log_normal_double(curandStateXORWOW_t *state, double mean, double stddev)
|
412 |
+
{
|
413 |
+
if(state->boxmuller_flag_double != EXTRA_FLAG_LOG_NORMAL) {
|
414 |
+
unsigned int x0, x1, y0, y1;
|
415 |
+
x0 = curand(state);
|
416 |
+
x1 = curand(state);
|
417 |
+
y0 = curand(state);
|
418 |
+
y1 = curand(state);
|
419 |
+
double2 v = _curand_box_muller_double(x0, x1, y0, y1);
|
420 |
+
state->boxmuller_extra_double = exp(mean + (stddev * v.y));
|
421 |
+
state->boxmuller_flag_double = EXTRA_FLAG_LOG_NORMAL;
|
422 |
+
return exp(mean + (stddev * v.x));
|
423 |
+
}
|
424 |
+
state->boxmuller_flag_double = 0;
|
425 |
+
return state->boxmuller_extra_double;
|
426 |
+
}
|
427 |
+
|
428 |
+
/**
|
429 |
+
* \brief Return a log-normally distributed double from an Philox4_32_10 generator.
|
430 |
+
*
|
431 |
+
* Return a single normally distributed double derived from a normal
|
432 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
433 |
+
* from the Philox4_32_10 generator in \p state,
|
434 |
+
* increment position of generator.
|
435 |
+
*
|
436 |
+
* The implementation uses a Box-Muller transform to generate two
|
437 |
+
* normally distributed results, transforms them to log-normal distribution,
|
438 |
+
* then returns them one at a time.
|
439 |
+
* See ::curand_log_normal2_double() for a more efficient version that returns
|
440 |
+
* both results at once.
|
441 |
+
*
|
442 |
+
* \param state - Pointer to state to update
|
443 |
+
* \param mean - Mean of the related normal distribution
|
444 |
+
* \param stddev - Standard deviation of the related normal distribution
|
445 |
+
*
|
446 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
447 |
+
*/
|
448 |
+
|
449 |
+
QUALIFIERS double curand_log_normal_double(curandStatePhilox4_32_10_t *state, double mean, double stddev)
|
450 |
+
{
|
451 |
+
if(state->boxmuller_flag_double != EXTRA_FLAG_LOG_NORMAL) {
|
452 |
+
uint4 _x;
|
453 |
+
_x = curand4(state);
|
454 |
+
double2 v = _curand_box_muller_double(_x.x, _x.y, _x.z, _x.w);
|
455 |
+
state->boxmuller_extra_double = exp(mean + (stddev * v.y));
|
456 |
+
state->boxmuller_flag_double = EXTRA_FLAG_LOG_NORMAL;
|
457 |
+
return exp(mean + (stddev * v.x));
|
458 |
+
}
|
459 |
+
state->boxmuller_flag_double = 0;
|
460 |
+
return state->boxmuller_extra_double;
|
461 |
+
}
|
462 |
+
|
463 |
+
|
464 |
+
/**
|
465 |
+
* \brief Return two log-normally distributed doubles from an XORWOW generator.
|
466 |
+
*
|
467 |
+
* Return two log-normally distributed doubles derived from a normal
|
468 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
469 |
+
* from the XORWOW generator in \p state,
|
470 |
+
* increment position of generator by two.
|
471 |
+
*
|
472 |
+
* The implementation uses a Box-Muller transform to generate two
|
473 |
+
* normally distributed results, and transforms them to log-normal distribution,.
|
474 |
+
*
|
475 |
+
* \param state - Pointer to state to update
|
476 |
+
* \param mean - Mean of the related normal distribution
|
477 |
+
* \param stddev - Standard deviation of the related normal distribution
|
478 |
+
*
|
479 |
+
* \return Log-normally distributed double2 where each element is from a
|
480 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
481 |
+
*/
|
482 |
+
QUALIFIERS double2 curand_log_normal2_double(curandStateXORWOW_t *state, double mean, double stddev)
|
483 |
+
{
|
484 |
+
double2 v = curand_box_muller_double(state);
|
485 |
+
v.x = exp(mean + (stddev * v.x));
|
486 |
+
v.y = exp(mean + (stddev * v.y));
|
487 |
+
return v;
|
488 |
+
}
|
489 |
+
|
490 |
+
/**
|
491 |
+
* \brief Return two log-normally distributed doubles from an Philox4_32_10 generator.
|
492 |
+
*
|
493 |
+
* Return two log-normally distributed doubles derived from a normal
|
494 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
495 |
+
* from the Philox4_32_10 generator in \p state,
|
496 |
+
* increment position of generator by four.
|
497 |
+
*
|
498 |
+
* The implementation uses a Box-Muller transform to generate two
|
499 |
+
* normally distributed results, and transforms them to log-normal distribution,.
|
500 |
+
*
|
501 |
+
* \param state - Pointer to state to update
|
502 |
+
* \param mean - Mean of the related normal distribution
|
503 |
+
* \param stddev - Standard deviation of the related normal distribution
|
504 |
+
*
|
505 |
+
* \return Log-normally distributed double4 where each element is from a
|
506 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
507 |
+
*/
|
508 |
+
QUALIFIERS double2 curand_log_normal2_double(curandStatePhilox4_32_10_t *state, double mean, double stddev)
|
509 |
+
{
|
510 |
+
double2 v = curand_box_muller2_double(state);
|
511 |
+
v.x = exp(mean + (stddev * v.x));
|
512 |
+
v.y = exp(mean + (stddev * v.y));
|
513 |
+
return v;
|
514 |
+
}
|
515 |
+
// nor part of API
|
516 |
+
QUALIFIERS double4 curand_log_normal4_double(curandStatePhilox4_32_10_t *state, double mean, double stddev)
|
517 |
+
{
|
518 |
+
double4 v = curand_box_muller4_double(state);
|
519 |
+
v.x = exp(mean + (stddev * v.x));
|
520 |
+
v.y = exp(mean + (stddev * v.y));
|
521 |
+
v.z = exp(mean + (stddev * v.z));
|
522 |
+
v.w = exp(mean + (stddev * v.w));
|
523 |
+
return v;
|
524 |
+
}
|
525 |
+
|
526 |
+
/**
|
527 |
+
* \brief Return a log-normally distributed double from an MRG32k3a generator.
|
528 |
+
*
|
529 |
+
* Return a single normally distributed double derived from a normal
|
530 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
531 |
+
* from the MRG32k3a generator in \p state,
|
532 |
+
* increment position of generator.
|
533 |
+
*
|
534 |
+
* The implementation uses a Box-Muller transform to generate two
|
535 |
+
* normally distributed results, transforms them to log-normal distribution,
|
536 |
+
* then returns them one at a time.
|
537 |
+
* See ::curand_log_normal2_double() for a more efficient version that returns
|
538 |
+
* both results at once.
|
539 |
+
*
|
540 |
+
* \param state - Pointer to state to update
|
541 |
+
* \param mean - Mean of the related normal distribution
|
542 |
+
* \param stddev - Standard deviation of the related normal distribution
|
543 |
+
*
|
544 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
545 |
+
*/
|
546 |
+
QUALIFIERS double curand_log_normal_double(curandStateMRG32k3a_t *state, double mean, double stddev)
|
547 |
+
{
|
548 |
+
if(state->boxmuller_flag_double != EXTRA_FLAG_LOG_NORMAL) {
|
549 |
+
double2 v = curand_box_muller_mrg_double(state);
|
550 |
+
state->boxmuller_extra_double = exp(mean + (stddev * v.y));
|
551 |
+
state->boxmuller_flag_double = EXTRA_FLAG_LOG_NORMAL;
|
552 |
+
return exp(mean + (stddev * v.x));
|
553 |
+
}
|
554 |
+
state->boxmuller_flag_double = 0;
|
555 |
+
return state->boxmuller_extra_double;
|
556 |
+
}
|
557 |
+
|
558 |
+
/**
|
559 |
+
* \brief Return two log-normally distributed doubles from an MRG32k3a generator.
|
560 |
+
*
|
561 |
+
* Return two log-normally distributed doubles derived from a normal
|
562 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
563 |
+
* from the MRG32k3a generator in \p state,
|
564 |
+
* increment position of generator by two.
|
565 |
+
*
|
566 |
+
* The implementation uses a Box-Muller transform to generate two
|
567 |
+
* normally distributed results, and transforms them to log-normal distribution,.
|
568 |
+
*
|
569 |
+
* \param state - Pointer to state to update
|
570 |
+
* \param mean - Mean of the related normal distribution
|
571 |
+
* \param stddev - Standard deviation of the related normal distribution
|
572 |
+
*
|
573 |
+
* \return Log-normally distributed double2 where each element is from a
|
574 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
575 |
+
*/
|
576 |
+
QUALIFIERS double2 curand_log_normal2_double(curandStateMRG32k3a_t *state, double mean, double stddev)
|
577 |
+
{
|
578 |
+
double2 v = curand_box_muller_mrg_double(state);
|
579 |
+
v.x = exp(mean + (stddev * v.x));
|
580 |
+
v.y = exp(mean + (stddev * v.y));
|
581 |
+
return v;
|
582 |
+
}
|
583 |
+
|
584 |
+
/**
|
585 |
+
* \brief Return a log-normally distributed double from an MTGP32 generator.
|
586 |
+
*
|
587 |
+
* Return a single log-normally distributed double derived from a normal
|
588 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
589 |
+
* from the MTGP32 generator in \p state,
|
590 |
+
* increment position of generator.
|
591 |
+
*
|
592 |
+
* The implementation uses the inverse cumulative distribution function
|
593 |
+
* to generate normally distributed results, and transforms them into
|
594 |
+
* log-normal distribution.
|
595 |
+
*
|
596 |
+
* \param state - Pointer to state to update
|
597 |
+
* \param mean - Mean of the related normal distribution
|
598 |
+
* \param stddev - Standard deviation of the related normal distribution
|
599 |
+
*
|
600 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
601 |
+
*/
|
602 |
+
QUALIFIERS double curand_log_normal_double(curandStateMtgp32_t *state, double mean, double stddev)
|
603 |
+
{
|
604 |
+
return exp(mean + (stddev * _curand_normal_icdf_double(curand(state))));
|
605 |
+
}
|
606 |
+
|
607 |
+
/**
|
608 |
+
* \brief Return a log-normally distributed double from a Sobol32 generator.
|
609 |
+
*
|
610 |
+
* Return a single log-normally distributed double derived from a normal
|
611 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
612 |
+
* from the Sobol32 generator in \p state,
|
613 |
+
* increment position of generator by one.
|
614 |
+
*
|
615 |
+
* The implementation uses the inverse cumulative distribution function
|
616 |
+
* to generate normally distributed results, and transforms them into
|
617 |
+
* log-normal distribution.
|
618 |
+
*
|
619 |
+
* \param state - Pointer to state to update
|
620 |
+
* \param mean - Mean of the related normal distribution
|
621 |
+
* \param stddev - Standard deviation of the related normal distribution
|
622 |
+
*
|
623 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
624 |
+
*/
|
625 |
+
QUALIFIERS double curand_log_normal_double(curandStateSobol32_t *state, double mean, double stddev)
|
626 |
+
{
|
627 |
+
return exp(mean + (stddev * _curand_normal_icdf_double(curand(state))));
|
628 |
+
}
|
629 |
+
|
630 |
+
/**
|
631 |
+
* \brief Return a log-normally distributed double from a scrambled Sobol32 generator.
|
632 |
+
*
|
633 |
+
* Return a single log-normally distributed double derived from a normal
|
634 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
635 |
+
* from the scrambled Sobol32 generator in \p state,
|
636 |
+
* increment position of generator by one.
|
637 |
+
*
|
638 |
+
* The implementation uses the inverse cumulative distribution function
|
639 |
+
* to generate normally distributed results, and transforms them into
|
640 |
+
* log-normal distribution.
|
641 |
+
*
|
642 |
+
* \param state - Pointer to state to update
|
643 |
+
* \param mean - Mean of the related normal distribution
|
644 |
+
* \param stddev - Standard deviation of the related normal distribution
|
645 |
+
*
|
646 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
647 |
+
*/
|
648 |
+
QUALIFIERS double curand_log_normal_double(curandStateScrambledSobol32_t *state, double mean, double stddev)
|
649 |
+
{
|
650 |
+
return exp(mean + (stddev * _curand_normal_icdf_double(curand(state))));
|
651 |
+
}
|
652 |
+
|
653 |
+
/**
|
654 |
+
* \brief Return a log-normally distributed double from a Sobol64 generator.
|
655 |
+
*
|
656 |
+
* Return a single normally distributed double derived from a normal
|
657 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
658 |
+
* from the Sobol64 generator in \p state,
|
659 |
+
* increment position of generator by one.
|
660 |
+
*
|
661 |
+
* The implementation uses the inverse cumulative distribution function
|
662 |
+
* to generate normally distributed results.
|
663 |
+
*
|
664 |
+
* \param state - Pointer to state to update
|
665 |
+
* \param mean - Mean of the related normal distribution
|
666 |
+
* \param stddev - Standard deviation of the related normal distribution
|
667 |
+
*
|
668 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
669 |
+
*/
|
670 |
+
QUALIFIERS double curand_log_normal_double(curandStateSobol64_t *state, double mean, double stddev)
|
671 |
+
{
|
672 |
+
return exp(mean + (stddev * _curand_normal_icdf_double(curand(state))));
|
673 |
+
}
|
674 |
+
|
675 |
+
/**
|
676 |
+
* \brief Return a log-normally distributed double from a scrambled Sobol64 generator.
|
677 |
+
*
|
678 |
+
* Return a single normally distributed double derived from a normal
|
679 |
+
* distribution with mean \p mean and standard deviation \p stddev
|
680 |
+
* from the scrambled Sobol64 generator in \p state,
|
681 |
+
* increment position of generator by one.
|
682 |
+
*
|
683 |
+
* The implementation uses the inverse cumulative distribution function
|
684 |
+
* to generate normally distributed results.
|
685 |
+
*
|
686 |
+
* \param state - Pointer to state to update
|
687 |
+
* \param mean - Mean of the related normal distribution
|
688 |
+
* \param stddev - Standard deviation of the related normal distribution
|
689 |
+
*
|
690 |
+
* \return Log-normally distributed double with mean \p mean and standard deviation \p stddev
|
691 |
+
*/
|
692 |
+
QUALIFIERS double curand_log_normal_double(curandStateScrambledSobol64_t *state, double mean, double stddev)
|
693 |
+
{
|
694 |
+
return exp(mean + (stddev * _curand_normal_icdf_double(curand(state))));
|
695 |
+
}
|
696 |
+
|
697 |
+
#endif // !defined(CURAND_LOGNORMAL_H_)
|
llmeval-env/lib/python3.10/site-packages/nvidia/curand/include/curand_mtgp32_host.h
ADDED
@@ -0,0 +1,516 @@
|
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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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|
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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 |
+
/*
|
51 |
+
* curand_mtgp32_host.h
|
52 |
+
*
|
53 |
+
*
|
54 |
+
* MTGP32-11213
|
55 |
+
*
|
56 |
+
* Mersenne Twister RNG for the GPU
|
57 |
+
*
|
58 |
+
* The period of generated integers is 2<sup>11213</sup>-1.
|
59 |
+
*
|
60 |
+
* This code generates 32-bit unsigned integers, and
|
61 |
+
* single precision floating point numbers uniformly distributed
|
62 |
+
* in the range [1, 2). (float r; 1.0 <= r < 2.0)
|
63 |
+
*/
|
64 |
+
|
65 |
+
/*
|
66 |
+
* Copyright (c) 2009, 2010 Mutsuo Saito, Makoto Matsumoto and Hiroshima
|
67 |
+
* University. All rights reserved.
|
68 |
+
* Copyright (c) 2011 Mutsuo Saito, Makoto Matsumoto, Hiroshima
|
69 |
+
* University and University of Tokyo. All rights reserved.
|
70 |
+
*
|
71 |
+
* Redistribution and use in source and binary forms, with or without
|
72 |
+
* modification, are permitted provided that the following conditions are
|
73 |
+
* met:
|
74 |
+
*
|
75 |
+
* * Redistributions of source code must retain the above copyright
|
76 |
+
* notice, this list of conditions and the following disclaimer.
|
77 |
+
* * Redistributions in binary form must reproduce the above
|
78 |
+
* copyright notice, this list of conditions and the following
|
79 |
+
* disclaimer in the documentation and/or other materials provided
|
80 |
+
* with the distribution.
|
81 |
+
* * Neither the name of the Hiroshima University nor the names of
|
82 |
+
* its contributors may be used to endorse or promote products
|
83 |
+
* derived from this software without specific prior written
|
84 |
+
* permission.
|
85 |
+
*
|
86 |
+
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
87 |
+
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
88 |
+
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
89 |
+
* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
|
90 |
+
* OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
91 |
+
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
92 |
+
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
93 |
+
* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
94 |
+
* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
95 |
+
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
96 |
+
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
97 |
+
*/
|
98 |
+
#if !defined CURAND_MTGP32_HOST_H
|
99 |
+
#define CURAND_MTGP32_HOST_H
|
100 |
+
|
101 |
+
#if !defined(QUALIFIERS)
|
102 |
+
#define QUALIFIERS static inline __device__
|
103 |
+
#endif
|
104 |
+
|
105 |
+
#include <cuda_runtime.h>
|
106 |
+
#include <stdlib.h>
|
107 |
+
#include <memory.h>
|
108 |
+
#include <string.h>
|
109 |
+
#include "curand.h"
|
110 |
+
#include "curand_mtgp32.h"
|
111 |
+
#include "curand_mtgp32dc_p_11213.h"
|
112 |
+
|
113 |
+
|
114 |
+
/**
|
115 |
+
* \addtogroup DEVICE Device API
|
116 |
+
*
|
117 |
+
* @{
|
118 |
+
*/
|
119 |
+
|
120 |
+
static const unsigned int non_zero = 0x4d544750;
|
121 |
+
|
122 |
+
/*
|
123 |
+
* This function represents a function used in the initialization
|
124 |
+
* by mtgp32_init_by_array() and mtgp32_init_by_str().
|
125 |
+
* @param[in] x 32-bit integer
|
126 |
+
* @return 32-bit integer
|
127 |
+
*/
|
128 |
+
static __forceinline__ unsigned int ini_func1(unsigned int x) {
|
129 |
+
return (x ^ (x >> 27)) * (1664525);
|
130 |
+
}
|
131 |
+
|
132 |
+
/*
|
133 |
+
* This function represents a function used in the initialization
|
134 |
+
* by mtgp32_init_by_array() and mtgp32_init_by_str().
|
135 |
+
* @param[in] x 32-bit integer
|
136 |
+
* @return 32-bit integer
|
137 |
+
*/
|
138 |
+
static __forceinline__ unsigned int ini_func2(unsigned int x) {
|
139 |
+
return (x ^ (x >> 27)) * (1566083941);
|
140 |
+
}
|
141 |
+
|
142 |
+
/*
|
143 |
+
* This function initializes the internal state array with a 32-bit
|
144 |
+
* integer seed. The allocated memory should be freed by calling
|
145 |
+
* mtgp32_free(). \b para should be one of the elements in the
|
146 |
+
* parameter table (mtgp32-param-ref.c).
|
147 |
+
*
|
148 |
+
* This function is call by cuda program, because cuda program uses
|
149 |
+
* another structure and another allocation method.
|
150 |
+
*
|
151 |
+
* @param[out] array MTGP internal status vector.
|
152 |
+
* @param[in] para parameter structure
|
153 |
+
* @param[in] seed a 32-bit integer used as the seed.
|
154 |
+
*/
|
155 |
+
static __forceinline__ __host__
|
156 |
+
void mtgp32_init_state(unsigned int state[],
|
157 |
+
const mtgp32_params_fast_t *para, unsigned int seed) {
|
158 |
+
int i;
|
159 |
+
int size = para->mexp / 32 + 1;
|
160 |
+
unsigned int hidden_seed;
|
161 |
+
unsigned int tmp;
|
162 |
+
hidden_seed = para->tbl[4] ^ (para->tbl[8] << 16);
|
163 |
+
tmp = hidden_seed;
|
164 |
+
tmp += tmp >> 16;
|
165 |
+
tmp += tmp >> 8;
|
166 |
+
memset(state, tmp & 0xff, sizeof(unsigned int) * size);
|
167 |
+
state[0] = seed;
|
168 |
+
state[1] = hidden_seed;
|
169 |
+
for (i = 1; i < size; i++) {
|
170 |
+
state[i] ^= (1812433253) * (state[i - 1] ^ (state[i - 1] >> 30)) + i;
|
171 |
+
}
|
172 |
+
}
|
173 |
+
|
174 |
+
/*
|
175 |
+
* This function initializes the internal state array
|
176 |
+
* with a 32-bit integer array. \b para should be one of the elements in
|
177 |
+
* the parameter table (mtgp32-param-ref.c).
|
178 |
+
*
|
179 |
+
* @param[out] mtgp32 MTGP structure.
|
180 |
+
* @param[in] para parameter structure
|
181 |
+
* @param[in] array a 32-bit integer array used as a seed.
|
182 |
+
* @param[in] length length of the array.
|
183 |
+
* @return CURAND_STATUS_SUCCESS
|
184 |
+
*/
|
185 |
+
static __forceinline__ __host__
|
186 |
+
int mtgp32_init_by_array(unsigned int state[],
|
187 |
+
const mtgp32_params_fast_t *para,
|
188 |
+
unsigned int *array, int length) {
|
189 |
+
int i, j, count;
|
190 |
+
unsigned int r;
|
191 |
+
int lag;
|
192 |
+
int mid;
|
193 |
+
int size = para->mexp / 32 + 1;
|
194 |
+
unsigned int hidden_seed;
|
195 |
+
unsigned int tmp;
|
196 |
+
|
197 |
+
if (size >= 623) {
|
198 |
+
lag = 11;
|
199 |
+
} else if (size >= 68) {
|
200 |
+
lag = 7;
|
201 |
+
} else if (size >= 39) {
|
202 |
+
lag = 5;
|
203 |
+
} else {
|
204 |
+
lag = 3;
|
205 |
+
}
|
206 |
+
mid = (size - lag) / 2;
|
207 |
+
|
208 |
+
hidden_seed = para->tbl[4] ^ (para->tbl[8] << 16);
|
209 |
+
tmp = hidden_seed;
|
210 |
+
tmp += tmp >> 16;
|
211 |
+
tmp += tmp >> 8;
|
212 |
+
memset(state, tmp & 0xff, sizeof(unsigned int) * size);
|
213 |
+
state[0] = hidden_seed;
|
214 |
+
|
215 |
+
if (length + 1 > size) {
|
216 |
+
count = length + 1;
|
217 |
+
} else {
|
218 |
+
count = size;
|
219 |
+
}
|
220 |
+
r = ini_func1(state[0] ^ state[mid] ^ state[size - 1]);
|
221 |
+
state[mid] += r;
|
222 |
+
r += length;
|
223 |
+
state[(mid + lag) % size] += r;
|
224 |
+
state[0] = r;
|
225 |
+
i = 1;
|
226 |
+
count--;
|
227 |
+
for (i = 1, j = 0; (j < count) && (j < length); j++) {
|
228 |
+
r = ini_func1(state[i] ^ state[(i + mid) % size]
|
229 |
+
^ state[(i + size - 1) % size]);
|
230 |
+
state[(i + mid) % size] += r;
|
231 |
+
r += array[j] + i;
|
232 |
+
state[(i + mid + lag) % size] += r;
|
233 |
+
state[i] = r;
|
234 |
+
i = (i + 1) % size;
|
235 |
+
}
|
236 |
+
for (; j < count; j++) {
|
237 |
+
r = ini_func1(state[i] ^ state[(i + mid) % size]
|
238 |
+
^ state[(i + size - 1) % size]);
|
239 |
+
state[(i + mid) % size] += r;
|
240 |
+
r += i;
|
241 |
+
state[(i + mid + lag) % size] += r;
|
242 |
+
state[i] = r;
|
243 |
+
i = (i + 1) % size;
|
244 |
+
}
|
245 |
+
for (j = 0; j < size; j++) {
|
246 |
+
r = ini_func2(state[i] + state[(i + mid) % size]
|
247 |
+
+ state[(i + size - 1) % size]);
|
248 |
+
state[(i + mid) % size] ^= r;
|
249 |
+
r -= i;
|
250 |
+
state[(i + mid + lag) % size] ^= r;
|
251 |
+
state[i] = r;
|
252 |
+
i = (i + 1) % size;
|
253 |
+
}
|
254 |
+
if (state[size - 1] == 0) {
|
255 |
+
state[size - 1] = non_zero;
|
256 |
+
}
|
257 |
+
return 0;
|
258 |
+
}
|
259 |
+
|
260 |
+
/*
|
261 |
+
* This function initializes the internal state array
|
262 |
+
* with a character array. \b para should be one of the elements in
|
263 |
+
* the parameter table (mtgp32-param-ref.c).
|
264 |
+
* This is the same algorithm with mtgp32_init_by_array(), but hope to
|
265 |
+
* be more useful.
|
266 |
+
*
|
267 |
+
* @param[out] mtgp32 MTGP structure.
|
268 |
+
* @param[in] para parameter structure
|
269 |
+
* @param[in] array a character array used as a seed. (terminated by zero.)
|
270 |
+
* @return memory allocation result. if 0 then O.K.
|
271 |
+
*/
|
272 |
+
static __forceinline__ __host__
|
273 |
+
int mtgp32_init_by_str(unsigned int state[],
|
274 |
+
const mtgp32_params_fast_t *para, unsigned char *array) {
|
275 |
+
int i, j, count;
|
276 |
+
unsigned int r;
|
277 |
+
int lag;
|
278 |
+
int mid;
|
279 |
+
int size = para->mexp / 32 + 1;
|
280 |
+
int length = (unsigned int)strlen((char *)array);
|
281 |
+
unsigned int hidden_seed;
|
282 |
+
unsigned int tmp;
|
283 |
+
|
284 |
+
if (size >= 623) {
|
285 |
+
lag = 11;
|
286 |
+
} else if (size >= 68) {
|
287 |
+
lag = 7;
|
288 |
+
} else if (size >= 39) {
|
289 |
+
lag = 5;
|
290 |
+
} else {
|
291 |
+
lag = 3;
|
292 |
+
}
|
293 |
+
mid = (size - lag) / 2;
|
294 |
+
|
295 |
+
hidden_seed = para->tbl[4] ^ (para->tbl[8] << 16);
|
296 |
+
tmp = hidden_seed;
|
297 |
+
tmp += tmp >> 16;
|
298 |
+
tmp += tmp >> 8;
|
299 |
+
memset(state, tmp & 0xff, sizeof(unsigned int) * size);
|
300 |
+
state[0] = hidden_seed;
|
301 |
+
|
302 |
+
if (length + 1 > size) {
|
303 |
+
count = length + 1;
|
304 |
+
} else {
|
305 |
+
count = size;
|
306 |
+
}
|
307 |
+
r = ini_func1(state[0] ^ state[mid] ^ state[size - 1]);
|
308 |
+
state[mid] += r;
|
309 |
+
r += length;
|
310 |
+
state[(mid + lag) % size] += r;
|
311 |
+
state[0] = r;
|
312 |
+
i = 1;
|
313 |
+
count--;
|
314 |
+
for (i = 1, j = 0; (j < count) && (j < length); j++) {
|
315 |
+
r = ini_func1(state[i] ^ state[(i + mid) % size]
|
316 |
+
^ state[(i + size - 1) % size]);
|
317 |
+
state[(i + mid) % size] += r;
|
318 |
+
r += array[j] + i;
|
319 |
+
state[(i + mid + lag) % size] += r;
|
320 |
+
state[i] = r;
|
321 |
+
i = (i + 1) % size;
|
322 |
+
}
|
323 |
+
for (; j < count; j++) {
|
324 |
+
r = ini_func1(state[i] ^ state[(i + mid) % size]
|
325 |
+
^ state[(i + size - 1) % size]);
|
326 |
+
state[(i + mid) % size] += r;
|
327 |
+
r += i;
|
328 |
+
state[(i + mid + lag) % size] += r;
|
329 |
+
state[i] = r;
|
330 |
+
i = (i + 1) % size;
|
331 |
+
}
|
332 |
+
for (j = 0; j < size; j++) {
|
333 |
+
r = ini_func2(state[i] + state[(i + mid) % size]
|
334 |
+
+ state[(i + size - 1) % size]);
|
335 |
+
state[(i + mid) % size] ^= r;
|
336 |
+
r -= i;
|
337 |
+
state[(i + mid + lag) % size] ^= r;
|
338 |
+
state[i] = r;
|
339 |
+
i = (i + 1) % size;
|
340 |
+
}
|
341 |
+
if (state[size - 1] == 0) {
|
342 |
+
state[size - 1] = non_zero;
|
343 |
+
}
|
344 |
+
return 0;
|
345 |
+
}
|
346 |
+
|
347 |
+
template<typename ParamsType>
|
348 |
+
static __forceinline__ __host__
|
349 |
+
curandStatus_t curandMakeMTGP32ConstantsImpl(const mtgp32_params_fast_t params[], ParamsType * p, const int block_num)
|
350 |
+
{
|
351 |
+
const int size1 = sizeof(unsigned int) * block_num;
|
352 |
+
const int size2 = sizeof(unsigned int) * block_num * TBL_SIZE;
|
353 |
+
unsigned int *h_pos_tbl;
|
354 |
+
unsigned int *h_sh1_tbl;
|
355 |
+
unsigned int *h_sh2_tbl;
|
356 |
+
unsigned int *h_param_tbl;
|
357 |
+
unsigned int *h_temper_tbl;
|
358 |
+
unsigned int *h_single_temper_tbl;
|
359 |
+
unsigned int *h_mask;
|
360 |
+
curandStatus_t status = CURAND_STATUS_SUCCESS;
|
361 |
+
|
362 |
+
h_pos_tbl = (unsigned int *)malloc(size1);
|
363 |
+
h_sh1_tbl = (unsigned int *)malloc(size1);
|
364 |
+
h_sh2_tbl = (unsigned int *)malloc(size1);
|
365 |
+
h_param_tbl = (unsigned int *)malloc(size2);
|
366 |
+
h_temper_tbl = (unsigned int *)malloc(size2);
|
367 |
+
h_single_temper_tbl = (unsigned int *)malloc(size2);
|
368 |
+
h_mask = (unsigned int *)malloc(sizeof(unsigned int));
|
369 |
+
if (h_pos_tbl == NULL
|
370 |
+
|| h_sh1_tbl == NULL
|
371 |
+
|| h_sh2_tbl == NULL
|
372 |
+
|| h_param_tbl == NULL
|
373 |
+
|| h_temper_tbl == NULL
|
374 |
+
|| h_single_temper_tbl == NULL
|
375 |
+
|| h_mask == NULL) {
|
376 |
+
if (h_pos_tbl != NULL) free(h_pos_tbl);
|
377 |
+
if (h_sh1_tbl != NULL) free(h_sh1_tbl);
|
378 |
+
if (h_sh2_tbl != NULL) free(h_sh2_tbl);
|
379 |
+
if (h_param_tbl != NULL) free(h_param_tbl);
|
380 |
+
if (h_temper_tbl != NULL) free(h_temper_tbl);
|
381 |
+
if (h_single_temper_tbl != NULL) free(h_single_temper_tbl);
|
382 |
+
if (h_mask != NULL) free(h_mask);
|
383 |
+
status = CURAND_STATUS_ALLOCATION_FAILED;
|
384 |
+
} else {
|
385 |
+
|
386 |
+
h_mask[0] = params[0].mask;
|
387 |
+
for (int i = 0; i < block_num; i++) {
|
388 |
+
h_pos_tbl[i] = params[i].pos;
|
389 |
+
h_sh1_tbl[i] = params[i].sh1;
|
390 |
+
h_sh2_tbl[i] = params[i].sh2;
|
391 |
+
for (int j = 0; j < TBL_SIZE; j++) {
|
392 |
+
h_param_tbl[i * TBL_SIZE + j] = params[i].tbl[j];
|
393 |
+
h_temper_tbl[i * TBL_SIZE + j] = params[i].tmp_tbl[j];
|
394 |
+
h_single_temper_tbl[i * TBL_SIZE + j] = params[i].flt_tmp_tbl[j];
|
395 |
+
}
|
396 |
+
}
|
397 |
+
if (cudaMemcpy( p->pos_tbl,
|
398 |
+
h_pos_tbl, size1, cudaMemcpyHostToDevice) != cudaSuccess)
|
399 |
+
{
|
400 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
401 |
+
} else
|
402 |
+
if (cudaMemcpy( p->sh1_tbl,
|
403 |
+
h_sh1_tbl, size1, cudaMemcpyHostToDevice) != cudaSuccess)
|
404 |
+
{
|
405 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
406 |
+
} else
|
407 |
+
if (cudaMemcpy( p->sh2_tbl,
|
408 |
+
h_sh2_tbl, size1, cudaMemcpyHostToDevice) != cudaSuccess)
|
409 |
+
{
|
410 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
411 |
+
} else
|
412 |
+
if (cudaMemcpy( p->param_tbl,
|
413 |
+
h_param_tbl, size2, cudaMemcpyHostToDevice) != cudaSuccess)
|
414 |
+
{
|
415 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
416 |
+
} else
|
417 |
+
if (cudaMemcpy( p->temper_tbl,
|
418 |
+
h_temper_tbl, size2, cudaMemcpyHostToDevice) != cudaSuccess)
|
419 |
+
{
|
420 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
421 |
+
} else
|
422 |
+
if (cudaMemcpy( p->single_temper_tbl,
|
423 |
+
h_single_temper_tbl, size2, cudaMemcpyHostToDevice) != cudaSuccess)
|
424 |
+
{
|
425 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
426 |
+
} else
|
427 |
+
if (cudaMemcpy( p->mask,
|
428 |
+
h_mask, sizeof(unsigned int), cudaMemcpyHostToDevice) != cudaSuccess)
|
429 |
+
{
|
430 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
431 |
+
}
|
432 |
+
}
|
433 |
+
if (h_pos_tbl != NULL) free(h_pos_tbl);
|
434 |
+
if (h_sh1_tbl != NULL) free(h_sh1_tbl);
|
435 |
+
if (h_sh2_tbl != NULL) free(h_sh2_tbl);
|
436 |
+
if (h_param_tbl != NULL) free(h_param_tbl);
|
437 |
+
if (h_temper_tbl != NULL) free(h_temper_tbl);
|
438 |
+
if (h_single_temper_tbl != NULL)free(h_single_temper_tbl);
|
439 |
+
if (h_mask != NULL) free(h_mask);
|
440 |
+
return status;
|
441 |
+
}
|
442 |
+
|
443 |
+
/**
|
444 |
+
* \brief Set up constant parameters for the mtgp32 generator
|
445 |
+
*
|
446 |
+
* This host-side helper function re-organizes CURAND_NUM_MTGP32_PARAMS sets of
|
447 |
+
* generator parameters for use by kernel functions and copies the
|
448 |
+
* result to the specified location in device memory.
|
449 |
+
*
|
450 |
+
* \param params - Pointer to an array of type mtgp32_params_fast_t in host memory
|
451 |
+
* \param p - pointer to a structure of type mtgp32_kernel_params_t in device memory.
|
452 |
+
*
|
453 |
+
* \return
|
454 |
+
* - CURAND_STATUS_ALLOCATION_FAILED if host memory could not be allocated
|
455 |
+
* - CURAND_STATUS_INITIALIZATION_FAILED if the copy to device memory failed
|
456 |
+
* - CURAND_STATUS_SUCCESS otherwise
|
457 |
+
*/
|
458 |
+
static __forceinline__ __host__
|
459 |
+
curandStatus_t curandMakeMTGP32Constants(const mtgp32_params_fast_t params[], mtgp32_kernel_params_t * p)
|
460 |
+
{
|
461 |
+
return curandMakeMTGP32ConstantsImpl(params, p, CURAND_NUM_MTGP32_PARAMS);
|
462 |
+
}
|
463 |
+
|
464 |
+
/**
|
465 |
+
* \brief Set up initial states for the mtgp32 generator
|
466 |
+
*
|
467 |
+
* This host-side helper function initializes a number of states (one parameter set per state) for
|
468 |
+
* an mtgp32 generator. To accomplish this it allocates a state array in host memory,
|
469 |
+
* initializes that array, and copies the result to device memory.
|
470 |
+
*
|
471 |
+
* \param s - pointer to an array of states in device memory
|
472 |
+
* \param params - Pointer to an array of type mtgp32_params_fast_t in host memory
|
473 |
+
* \param k - pointer to a structure of type mtgp32_kernel_params_t in device memory
|
474 |
+
* \param n - number of parameter sets/states to initialize
|
475 |
+
* \param seed - seed value
|
476 |
+
*
|
477 |
+
* \return
|
478 |
+
* - CURAND_STATUS_ALLOCATION_FAILED if host memory state could not be allocated
|
479 |
+
* - CURAND_STATUS_INITIALIZATION_FAILED if the copy to device memory failed
|
480 |
+
* - CURAND_STATUS_SUCCESS otherwise
|
481 |
+
*/
|
482 |
+
static __forceinline__ __host__
|
483 |
+
curandStatus_t CURANDAPI curandMakeMTGP32KernelState(curandStateMtgp32_t *s,
|
484 |
+
mtgp32_params_fast_t params[],
|
485 |
+
mtgp32_kernel_params_t *k,
|
486 |
+
int n,
|
487 |
+
unsigned long long seed)
|
488 |
+
{
|
489 |
+
int i;
|
490 |
+
curandStatus_t status = CURAND_STATUS_SUCCESS;
|
491 |
+
curandStateMtgp32_t *h_status =(curandStateMtgp32_t *) malloc(sizeof(curandStateMtgp32_t) * n);
|
492 |
+
if (h_status == NULL) {
|
493 |
+
status = CURAND_STATUS_ALLOCATION_FAILED;
|
494 |
+
} else {
|
495 |
+
seed = seed ^ (seed >> 32);
|
496 |
+
for (i = 0; i < n; i++) {
|
497 |
+
mtgp32_init_state(&(h_status[i].s[0]), ¶ms[i],(unsigned int)seed + i + 1);
|
498 |
+
h_status[i].offset = 0;
|
499 |
+
h_status[i].pIdx = i;
|
500 |
+
h_status[i].k = k;
|
501 |
+
}
|
502 |
+
if (cudaMemcpy(s, h_status,
|
503 |
+
sizeof(curandStateMtgp32_t) * n,
|
504 |
+
cudaMemcpyHostToDevice) != cudaSuccess) {
|
505 |
+
status = CURAND_STATUS_INITIALIZATION_FAILED;
|
506 |
+
}
|
507 |
+
}
|
508 |
+
free(h_status);
|
509 |
+
return status;
|
510 |
+
}
|
511 |
+
|
512 |
+
/** @} */
|
513 |
+
|
514 |
+
#endif
|
515 |
+
|
516 |
+
|
llmeval-env/lib/python3.10/site-packages/nvidia/curand/include/curand_mtgp32_kernel.h
ADDED
@@ -0,0 +1,386 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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 |
+
/*
|
51 |
+
* curand_mtgp32_kernel.h
|
52 |
+
*
|
53 |
+
*
|
54 |
+
* MTGP32-11213
|
55 |
+
*
|
56 |
+
* Mersenne Twister RNG for the GPU
|
57 |
+
*
|
58 |
+
* The period of generated integers is 2<sup>11213</sup>-1.
|
59 |
+
*
|
60 |
+
* This code generates 32-bit unsigned integers, and
|
61 |
+
* single precision floating point numbers uniformly distributed
|
62 |
+
* in the range [1, 2). (float r; 1.0 <= r < 2.0)
|
63 |
+
*/
|
64 |
+
|
65 |
+
/*
|
66 |
+
* Copyright (c) 2009, 2010 Mutsuo Saito, Makoto Matsumoto and Hiroshima
|
67 |
+
* University. All rights reserved.
|
68 |
+
* Copyright (c) 2011 Mutsuo Saito, Makoto Matsumoto, Hiroshima
|
69 |
+
* University and University of Tokyo. All rights reserved.
|
70 |
+
*
|
71 |
+
* Redistribution and use in source and binary forms, with or without
|
72 |
+
* modification, are permitted provided that the following conditions are
|
73 |
+
* met:
|
74 |
+
*
|
75 |
+
* * Redistributions of source code must retain the above copyright
|
76 |
+
* notice, this list of conditions and the following disclaimer.
|
77 |
+
* * Redistributions in binary form must reproduce the above
|
78 |
+
* copyright notice, this list of conditions and the following
|
79 |
+
* disclaimer in the documentation and/or other materials provided
|
80 |
+
* with the distribution.
|
81 |
+
* * Neither the name of the Hiroshima University nor the names of
|
82 |
+
* its contributors may be used to endorse or promote products
|
83 |
+
* derived from this software without specific prior written
|
84 |
+
* permission.
|
85 |
+
*
|
86 |
+
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
87 |
+
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
88 |
+
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
89 |
+
* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
|
90 |
+
* OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
91 |
+
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
92 |
+
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
93 |
+
* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
94 |
+
* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
95 |
+
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
96 |
+
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
97 |
+
*/
|
98 |
+
#if !defined CURAND_MTGP32_KERNEL_H
|
99 |
+
#define CURAND_MTGP32_KERNEL_H
|
100 |
+
|
101 |
+
#if !defined(QUALIFIERS)
|
102 |
+
#define QUALIFIERS static __forceinline__ __device__
|
103 |
+
#endif
|
104 |
+
|
105 |
+
#ifndef __CUDACC_RTC__
|
106 |
+
#include <cuda_runtime.h>
|
107 |
+
#include <stdlib.h>
|
108 |
+
#include <memory.h>
|
109 |
+
#include <string.h>
|
110 |
+
#endif // ifndef __CUDACC_RTC__
|
111 |
+
#include <nv/target>
|
112 |
+
#include "curand.h"
|
113 |
+
#include "curand_mtgp32.h"
|
114 |
+
|
115 |
+
/**
|
116 |
+
* \addtogroup DEVICE Device API
|
117 |
+
*
|
118 |
+
* @{
|
119 |
+
*/
|
120 |
+
|
121 |
+
#ifndef __CUDA_ARCH__
|
122 |
+
// define blockDim and threadIdx for host compatibility call
|
123 |
+
extern const dim3 blockDim;
|
124 |
+
extern const uint3 threadIdx;
|
125 |
+
#endif
|
126 |
+
|
127 |
+
|
128 |
+
/*
|
129 |
+
* The function of the recursion formula calculation.
|
130 |
+
*
|
131 |
+
* @param[in] X1 the farthest part of state array.
|
132 |
+
* @param[in] X2 the second farthest part of state array.
|
133 |
+
* @param[in] Y a part of state array.
|
134 |
+
* @param[in] bid block id.
|
135 |
+
* @return output
|
136 |
+
*/
|
137 |
+
QUALIFIERS unsigned int para_rec(mtgp32_kernel_params_t * k,unsigned int X1, unsigned int X2, unsigned int Y, int bid) {
|
138 |
+
unsigned int X = (X1 & k->mask[0]) ^ X2;
|
139 |
+
unsigned int MAT;
|
140 |
+
|
141 |
+
X ^= X << k->sh1_tbl[bid];
|
142 |
+
Y = X ^ (Y >> k->sh2_tbl[bid]);
|
143 |
+
MAT = k->param_tbl[bid][Y & 0x0f];
|
144 |
+
return Y ^ MAT;
|
145 |
+
}
|
146 |
+
|
147 |
+
/*
|
148 |
+
* The tempering function.
|
149 |
+
*
|
150 |
+
* @param[in] V the output value should be tempered.
|
151 |
+
* @param[in] T the tempering helper value.
|
152 |
+
* @param[in] bid block id.
|
153 |
+
* @return the tempered value.
|
154 |
+
*/
|
155 |
+
QUALIFIERS unsigned int temper(mtgp32_kernel_params_t * k,unsigned int V, unsigned int T, int bid) {
|
156 |
+
unsigned int MAT;
|
157 |
+
|
158 |
+
T ^= T >> 16;
|
159 |
+
T ^= T >> 8;
|
160 |
+
MAT = k->temper_tbl[bid][T & 0x0f];
|
161 |
+
return V ^ MAT;
|
162 |
+
}
|
163 |
+
|
164 |
+
/*
|
165 |
+
* The tempering and converting function.
|
166 |
+
* By using the preset table, converting to IEEE format
|
167 |
+
* and tempering are done simultaneously.
|
168 |
+
*
|
169 |
+
* @param[in] V the output value should be tempered.
|
170 |
+
* @param[in] T the tempering helper value.
|
171 |
+
* @param[in] bid block id.
|
172 |
+
* @return the tempered and converted value.
|
173 |
+
*/
|
174 |
+
QUALIFIERS unsigned int temper_single(mtgp32_kernel_params_t * k,unsigned int V, unsigned int T, int bid) {
|
175 |
+
unsigned int MAT;
|
176 |
+
unsigned int r;
|
177 |
+
|
178 |
+
T ^= T >> 16;
|
179 |
+
T ^= T >> 8;
|
180 |
+
MAT = k->single_temper_tbl[bid][T & 0x0f];
|
181 |
+
r = (V >> 9) ^ MAT;
|
182 |
+
return r;
|
183 |
+
}
|
184 |
+
|
185 |
+
/**
|
186 |
+
* \brief Return 32-bits of pseudorandomness from a mtgp32 generator.
|
187 |
+
*
|
188 |
+
* Return 32-bits of pseudorandomness from the mtgp32 generator in \p state,
|
189 |
+
* increment position of generator by the number of threads in the block.
|
190 |
+
* Note the number of threads in the block can not exceed 256.
|
191 |
+
*
|
192 |
+
* \param state - Pointer to state to update
|
193 |
+
*
|
194 |
+
* \return 32-bits of pseudorandomness as an unsigned int, all bits valid to use.
|
195 |
+
*/
|
196 |
+
QUALIFIERS unsigned int curand(curandStateMtgp32_t *state)
|
197 |
+
{
|
198 |
+
unsigned int t;
|
199 |
+
unsigned int d;
|
200 |
+
int pos = state->k->pos_tbl[state->pIdx];
|
201 |
+
unsigned int r;
|
202 |
+
unsigned int o;
|
203 |
+
|
204 |
+
d = blockDim.z * blockDim.y * blockDim.x;
|
205 |
+
//assert( d <= 256 );
|
206 |
+
t = (blockDim.z * blockDim.y * threadIdx.z) + (blockDim.x * threadIdx.y) + threadIdx.x;
|
207 |
+
r = para_rec(state->k, state->s[(t + state->offset) & MTGP32_STATE_MASK],
|
208 |
+
state->s[(t + state->offset + 1) & MTGP32_STATE_MASK],
|
209 |
+
state->s[(t + state->offset + pos) & MTGP32_STATE_MASK],
|
210 |
+
state->pIdx);
|
211 |
+
|
212 |
+
state->s[(t + state->offset + MTGPDC_N) & MTGP32_STATE_MASK] = r;
|
213 |
+
o = temper(state->k, r,
|
214 |
+
state->s[(t + state->offset + pos -1) & MTGP32_STATE_MASK],
|
215 |
+
state->pIdx);
|
216 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
217 |
+
__syncthreads();
|
218 |
+
)
|
219 |
+
if (t == 0)
|
220 |
+
{
|
221 |
+
state->offset = (state->offset + d) & MTGP32_STATE_MASK;
|
222 |
+
}
|
223 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
224 |
+
__syncthreads();
|
225 |
+
)
|
226 |
+
return o;
|
227 |
+
|
228 |
+
}
|
229 |
+
/**
|
230 |
+
* \brief Return 32-bits of pseudorandomness from a specific position in a mtgp32 generator.
|
231 |
+
*
|
232 |
+
* Return 32-bits of pseudorandomness from position \p index of the mtgp32 generator in \p state,
|
233 |
+
* increment position of generator by \p n positions, which must be the total number of positions
|
234 |
+
* upddated in the state by the thread block, for this invocation.
|
235 |
+
*
|
236 |
+
* Note :
|
237 |
+
* Thread indices must range from 0...\ n - 1.
|
238 |
+
* The number of positions updated may not exceed 256.
|
239 |
+
* A thread block may update more than one state, but a given state may not be updated by more than one thread block.
|
240 |
+
*
|
241 |
+
* \param state - Pointer to state to update
|
242 |
+
* \param index - Index (0..255) of the position within the state to draw from and update
|
243 |
+
* \param n - The total number of postions in this state that are being updated by this invocation
|
244 |
+
*
|
245 |
+
* \return 32-bits of pseudorandomness as an unsigned int, all bits valid to use.
|
246 |
+
*/
|
247 |
+
QUALIFIERS unsigned int curand_mtgp32_specific(curandStateMtgp32_t *state, unsigned char index, unsigned char n)
|
248 |
+
{
|
249 |
+
unsigned int t;
|
250 |
+
int pos = state->k->pos_tbl[state->pIdx];
|
251 |
+
unsigned int r;
|
252 |
+
unsigned int o;
|
253 |
+
|
254 |
+
t = index;
|
255 |
+
r = para_rec(state->k, state->s[(t + state->offset) & MTGP32_STATE_MASK],
|
256 |
+
state->s[(t + state->offset + 1) & MTGP32_STATE_MASK],
|
257 |
+
state->s[(t + state->offset + pos) & MTGP32_STATE_MASK],
|
258 |
+
state->pIdx);
|
259 |
+
|
260 |
+
state->s[(t + state->offset + MTGPDC_N) & MTGP32_STATE_MASK] = r;
|
261 |
+
o = temper(state->k, r,
|
262 |
+
state->s[(t + state->offset + pos -1) & MTGP32_STATE_MASK],
|
263 |
+
state->pIdx);
|
264 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
265 |
+
__syncthreads();
|
266 |
+
)
|
267 |
+
if (index == 0)
|
268 |
+
{
|
269 |
+
state->offset = (state->offset + n) & MTGP32_STATE_MASK;
|
270 |
+
}
|
271 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
272 |
+
__syncthreads();
|
273 |
+
)
|
274 |
+
return o;
|
275 |
+
}
|
276 |
+
/**
|
277 |
+
* \brief Return a uniformly distributed float from a mtgp32 generator.
|
278 |
+
*
|
279 |
+
* Return a uniformly distributed float between \p 0.0f and \p 1.0f
|
280 |
+
* from the mtgp32 generator in \p state, increment position of generator.
|
281 |
+
* Output range excludes \p 0.0f but includes \p 1.0f. Denormalized floating
|
282 |
+
* point outputs are never returned.
|
283 |
+
*
|
284 |
+
* Note: This alternate derivation of a uniform float is provided for completeness
|
285 |
+
* with the original source
|
286 |
+
*
|
287 |
+
* \param state - Pointer to state to update
|
288 |
+
*
|
289 |
+
* \return uniformly distributed float between \p 0.0f and \p 1.0f
|
290 |
+
*/
|
291 |
+
QUALIFIERS float curand_mtgp32_single(curandStateMtgp32_t *state)
|
292 |
+
{
|
293 |
+
unsigned int t;
|
294 |
+
unsigned int d;
|
295 |
+
int pos = state->k->pos_tbl[state->pIdx];
|
296 |
+
unsigned int r;
|
297 |
+
unsigned int o_u;
|
298 |
+
float o_f;
|
299 |
+
|
300 |
+
|
301 |
+
t = blockDim.z * blockDim.y;
|
302 |
+
d = t * blockDim.x;
|
303 |
+
//assert( d <= 256 );
|
304 |
+
t += threadIdx.x;
|
305 |
+
r = para_rec(state->k, state->s[(t + state->offset) & MTGP32_STATE_MASK],
|
306 |
+
state->s[(t + state->offset + 1) & MTGP32_STATE_MASK],
|
307 |
+
state->s[(t + state->offset + pos) & MTGP32_STATE_MASK],
|
308 |
+
state->pIdx);
|
309 |
+
|
310 |
+
state->s[t] = r;
|
311 |
+
o_u = temper_single(state->k, r,
|
312 |
+
state->s[(t + state->offset + pos -1) & MTGP32_STATE_MASK],
|
313 |
+
state->pIdx);
|
314 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
315 |
+
__syncthreads();
|
316 |
+
)
|
317 |
+
if (threadIdx.x == 0)
|
318 |
+
{
|
319 |
+
state->offset = (state->offset + d) & MTGP32_STATE_MASK;
|
320 |
+
}
|
321 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
322 |
+
__syncthreads();
|
323 |
+
)
|
324 |
+
memcpy(&o_f, &o_u, sizeof(o_u));
|
325 |
+
return o_f;
|
326 |
+
}
|
327 |
+
|
328 |
+
/**
|
329 |
+
* \brief Return a uniformly distributed float from a specific position in a mtgp32 generator.
|
330 |
+
*
|
331 |
+
* Return a uniformly distributed float between \p 0.0f and \p 1.0f
|
332 |
+
* from position \p index of the mtgp32 generator in \p state, and
|
333 |
+
* increment position of generator by \p n positions, which must be the total number of positions
|
334 |
+
* upddated in the state by the thread block, for this invocation.
|
335 |
+
* Output range excludes \p 0.0f but includes \p 1.0f. Denormalized floating
|
336 |
+
* point outputs are never returned.
|
337 |
+
*
|
338 |
+
* Note 1:
|
339 |
+
* Thread indices must range from 0...\p n - 1.
|
340 |
+
* The number of positions updated may not exceed 256.
|
341 |
+
* A thread block may update more than one state, but a given state may not be updated by more than one thread block.
|
342 |
+
*
|
343 |
+
* Note 2: This alternate derivation of a uniform float is provided for completeness
|
344 |
+
* with the original source
|
345 |
+
*
|
346 |
+
* \param state - Pointer to state to update
|
347 |
+
* \param index - Index (0..255) of the position within the state to draw from and update
|
348 |
+
* \param n - The total number of postions in this state that are being updated by this invocation
|
349 |
+
*
|
350 |
+
* \return uniformly distributed float between \p 0.0f and \p 1.0f
|
351 |
+
*/
|
352 |
+
QUALIFIERS float curand_mtgp32_single_specific(curandStateMtgp32_t *state, unsigned char index, unsigned char n)
|
353 |
+
{
|
354 |
+
unsigned int t;
|
355 |
+
int pos = state->k->pos_tbl[state->pIdx];
|
356 |
+
unsigned int r;
|
357 |
+
unsigned int o_u;
|
358 |
+
float o_f;
|
359 |
+
|
360 |
+
t = index;
|
361 |
+
r = para_rec(state->k, state->s[(t + state->offset) & MTGP32_STATE_MASK],
|
362 |
+
state->s[(t + state->offset + 1) & MTGP32_STATE_MASK],
|
363 |
+
state->s[(t + state->offset + pos) & MTGP32_STATE_MASK],
|
364 |
+
state->pIdx);
|
365 |
+
|
366 |
+
state->s[t] = r;
|
367 |
+
o_u = temper_single(state->k, r,
|
368 |
+
state->s[(t + state->offset + pos -1) & MTGP32_STATE_MASK],
|
369 |
+
state->pIdx);
|
370 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
371 |
+
__syncthreads();
|
372 |
+
)
|
373 |
+
if (threadIdx.x == 0)
|
374 |
+
{
|
375 |
+
state->offset = (state->offset + n) & MTGP32_STATE_MASK;
|
376 |
+
}
|
377 |
+
NV_IF_TARGET(NV_IS_DEVICE,
|
378 |
+
__syncthreads();
|
379 |
+
)
|
380 |
+
memcpy(&o_f, &o_u, sizeof(o_u));
|
381 |
+
return o_f;
|
382 |
+
}
|
383 |
+
|
384 |
+
/** @} */
|
385 |
+
|
386 |
+
#endif
|