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| /****************************************************************************** | |
| * Copyright (c) 2011, Duane Merrill. All rights reserved. | |
| * Copyright (c) 2011-2018, NVIDIA CORPORATION. All rights reserved. | |
| * | |
| * Redistribution and use in source and binary forms, with or without | |
| * modification, are permitted provided that the following conditions are met: | |
| * * Redistributions of source code must retain the above copyright | |
| * notice, this list of conditions and the following disclaimer. | |
| * * Redistributions in binary form must reproduce the above copyright | |
| * notice, this list of conditions and the following disclaimer in the | |
| * documentation and/or other materials provided with the distribution. | |
| * * Neither the name of the NVIDIA CORPORATION nor the | |
| * names of its contributors may be used to endorse or promote products | |
| * derived from this software without specific prior written permission. | |
| * | |
| * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | |
| * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED | |
| * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE | |
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| * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. | |
| * | |
| ******************************************************************************/ | |
| /** | |
| * \file | |
| * cub::DeviceSpmv provides device-wide parallel operations for performing sparse-matrix * vector multiplication (SpMV). | |
| */ | |
| #pragma once | |
| #include <stdio.h> | |
| #include <iterator> | |
| #include <limits> | |
| #include "dispatch/dispatch_spmv_orig.cuh" | |
| #include "../config.cuh" | |
| /// Optional outer namespace(s) | |
| CUB_NS_PREFIX | |
| /// CUB namespace | |
| namespace cub { | |
| /** | |
| * \brief DeviceSpmv provides device-wide parallel operations for performing sparse-matrix * dense-vector multiplication (SpMV). | |
| * \ingroup SingleModule | |
| * | |
| * \par Overview | |
| * The [<em>SpMV computation</em>](http://en.wikipedia.org/wiki/Sparse_matrix-vector_multiplication) | |
| * performs the matrix-vector operation | |
| * <em>y</em> = <em>alpha</em>*<b>A</b>*<em>x</em> + <em>beta</em>*<em>y</em>, | |
| * where: | |
| * - <b>A</b> is an <em>m</em>x<em>n</em> sparse matrix whose non-zero structure is specified in | |
| * [<em>compressed-storage-row (CSR) format</em>](http://en.wikipedia.org/wiki/Sparse_matrix#Compressed_row_Storage_.28CRS_or_CSR.29) | |
| * (i.e., three arrays: <em>values</em>, <em>row_offsets</em>, and <em>column_indices</em>) | |
| * - <em>x</em> and <em>y</em> are dense vectors | |
| * - <em>alpha</em> and <em>beta</em> are scalar multiplicands | |
| * | |
| * \par Usage Considerations | |
| * \cdp_class{DeviceSpmv} | |
| * | |
| */ | |
| struct DeviceSpmv | |
| { | |
| /******************************************************************//** | |
| * \name CSR matrix operations | |
| *********************************************************************/ | |
| //@{ | |
| /** | |
| * \brief This function performs the matrix-vector operation <em>y</em> = <b>A</b>*<em>x</em>. | |
| * | |
| * \par Snippet | |
| * The code snippet below illustrates SpMV upon a 9x9 CSR matrix <b>A</b> | |
| * representing a 3x3 lattice (24 non-zeros). | |
| * | |
| * \par | |
| * \code | |
| * #include <cub/cub.cuh> // or equivalently <cub/device/device_spmv.cuh> | |
| * | |
| * // Declare, allocate, and initialize device-accessible pointers for input matrix A, input vector x, | |
| * // and output vector y | |
| * int num_rows = 9; | |
| * int num_cols = 9; | |
| * int num_nonzeros = 24; | |
| * | |
| * float* d_values; // e.g., [1, 1, 1, 1, 1, 1, 1, 1, | |
| * // 1, 1, 1, 1, 1, 1, 1, 1, | |
| * // 1, 1, 1, 1, 1, 1, 1, 1] | |
| * | |
| * int* d_column_indices; // e.g., [1, 3, 0, 2, 4, 1, 5, 0, | |
| * // 4, 6, 1, 3, 5, 7, 2, 4, | |
| * // 8, 3, 7, 4, 6, 8, 5, 7] | |
| * | |
| * int* d_row_offsets; // e.g., [0, 2, 5, 7, 10, 14, 17, 19, 22, 24] | |
| * | |
| * float* d_vector_x; // e.g., [1, 1, 1, 1, 1, 1, 1, 1, 1] | |
| * float* d_vector_y; // e.g., [ , , , , , , , , ] | |
| * ... | |
| * | |
| * // Determine temporary device storage requirements | |
| * void* d_temp_storage = NULL; | |
| * size_t temp_storage_bytes = 0; | |
| * cub::DeviceSpmv::CsrMV(d_temp_storage, temp_storage_bytes, d_values, | |
| * d_row_offsets, d_column_indices, d_vector_x, d_vector_y, | |
| * num_rows, num_cols, num_nonzeros, alpha, beta); | |
| * | |
| * // Allocate temporary storage | |
| * cudaMalloc(&d_temp_storage, temp_storage_bytes); | |
| * | |
| * // Run SpMV | |
| * cub::DeviceSpmv::CsrMV(d_temp_storage, temp_storage_bytes, d_values, | |
| * d_row_offsets, d_column_indices, d_vector_x, d_vector_y, | |
| * num_rows, num_cols, num_nonzeros, alpha, beta); | |
| * | |
| * // d_vector_y <-- [2, 3, 2, 3, 4, 3, 2, 3, 2] | |
| * | |
| * \endcode | |
| * | |
| * \tparam ValueT <b>[inferred]</b> Matrix and vector value type (e.g., /p float, /p double, etc.) | |
| */ | |
| template < | |
| typename ValueT> | |
| CUB_RUNTIME_FUNCTION | |
| static cudaError_t CsrMV( | |
| void* d_temp_storage, ///< [in] %Device-accessible allocation of temporary storage. When NULL, the required allocation size is written to \p temp_storage_bytes and no work is done. | |
| size_t& temp_storage_bytes, ///< [in,out] Reference to size in bytes of \p d_temp_storage allocation | |
| ValueT* d_values, ///< [in] Pointer to the array of \p num_nonzeros values of the corresponding nonzero elements of matrix <b>A</b>. | |
| int* d_row_offsets, ///< [in] Pointer to the array of \p m + 1 offsets demarcating the start of every row in \p d_column_indices and \p d_values (with the final entry being equal to \p num_nonzeros) | |
| int* d_column_indices, ///< [in] Pointer to the array of \p num_nonzeros column-indices of the corresponding nonzero elements of matrix <b>A</b>. (Indices are zero-valued.) | |
| ValueT* d_vector_x, ///< [in] Pointer to the array of \p num_cols values corresponding to the dense input vector <em>x</em> | |
| ValueT* d_vector_y, ///< [out] Pointer to the array of \p num_rows values corresponding to the dense output vector <em>y</em> | |
| int num_rows, ///< [in] number of rows of matrix <b>A</b>. | |
| int num_cols, ///< [in] number of columns of matrix <b>A</b>. | |
| int num_nonzeros, ///< [in] number of nonzero elements of matrix <b>A</b>. | |
| cudaStream_t stream = 0, ///< [in] <b>[optional]</b> CUDA stream to launch kernels within. Default is stream<sub>0</sub>. | |
| bool debug_synchronous = false) ///< [in] <b>[optional]</b> Whether or not to synchronize the stream after every kernel launch to check for errors. May cause significant slowdown. Default is \p false. | |
| { | |
| SpmvParams<ValueT, int> spmv_params; | |
| spmv_params.d_values = d_values; | |
| spmv_params.d_row_end_offsets = d_row_offsets + 1; | |
| spmv_params.d_column_indices = d_column_indices; | |
| spmv_params.d_vector_x = d_vector_x; | |
| spmv_params.d_vector_y = d_vector_y; | |
| spmv_params.num_rows = num_rows; | |
| spmv_params.num_cols = num_cols; | |
| spmv_params.num_nonzeros = num_nonzeros; | |
| spmv_params.alpha = 1.0; | |
| spmv_params.beta = 0.0; | |
| return DispatchSpmv<ValueT, int>::Dispatch( | |
| d_temp_storage, | |
| temp_storage_bytes, | |
| spmv_params, | |
| stream, | |
| debug_synchronous); | |
| } | |
| //@} end member group | |
| }; | |
| } // CUB namespace | |
| CUB_NS_POSTFIX // Optional outer namespace(s) | |