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sddmm_csr_example.c
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sddmm_csr_example.c
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/*
* Copyright 1993-2022 NVIDIA Corporation. All rights reserved.
*
* NOTICE TO LICENSEE:
*
* This source code and/or documentation ("Licensed Deliverables") are
* subject to NVIDIA intellectual property rights under U.S. and
* international Copyright laws.
*
* These Licensed Deliverables contained herein is PROPRIETARY and
* CONFIDENTIAL to NVIDIA and is being provided under the terms and
* conditions of a form of NVIDIA software license agreement by and
* between NVIDIA and Licensee ("License Agreement") or electronically
* accepted by Licensee. Notwithstanding any terms or conditions to
* the contrary in the License Agreement, reproduction or disclosure
* of the Licensed Deliverables to any third party without the express
* written consent of NVIDIA is prohibited.
*
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
* OF THESE LICENSED DELIVERABLES.
*
* U.S. Government End Users. These Licensed Deliverables are a
* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
* 1995), consisting of "commercial computer software" and "commercial
* computer software documentation" as such terms are used in 48
* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
* U.S. Government End Users acquire the Licensed Deliverables with
* only those rights set forth herein.
*
* Any use of the Licensed Deliverables in individual and commercial
* software must include, in the user documentation and internal
* comments to the code, the above Disclaimer and U.S. Government End
* Users Notice.
*/
#include <cuda_runtime_api.h> // cudaMalloc, cudaMemcpy, etc.
#include <cusparse.h> // cusparseSpMM
#include <stdio.h> // printf
#include <stdlib.h> // EXIT_FAILURE
#define CHECK_CUDA(func) \
{ \
cudaError_t status = (func); \
if (status != cudaSuccess) { \
printf("CUDA API failed at line %d with error: %s (%d)\n", \
__LINE__, cudaGetErrorString(status), status); \
return EXIT_FAILURE; \
} \
}
#define CHECK_CUSPARSE(func) \
{ \
cusparseStatus_t status = (func); \
if (status != CUSPARSE_STATUS_SUCCESS) { \
printf("CUSPARSE API failed at line %d with error: %s (%d)\n", \
__LINE__, cusparseGetErrorString(status), status); \
return EXIT_FAILURE; \
} \
}
int main(void) {
// Host problem definition
int A_num_rows = 4;
int A_num_cols = 4;
int B_num_rows = A_num_cols;
int B_num_cols = 3;
int C_nnz = 9;
int lda = A_num_cols;
int ldb = B_num_cols;
int A_size = lda * A_num_rows;
int B_size = ldb * B_num_rows;
float hA[] = { 1.0f, 2.0f, 3.0f, 4.0f,
5.0f, 6.0f, 7.0f, 8.0f,
9.0f, 10.0f, 11.0f, 12.0f,
13.0f, 14.0f, 15.0f, 16.0f };
float hB[] = { 1.0f, 2.0f, 3.0f,
4.0f, 5.0f, 6.0f,
7.0f, 8.0f, 9.0f,
10.0f, 11.0f, 12.0f };
int hC_offsets[] = { 0, 3, 4, 7, 9 };
int hC_columns[] = { 0, 1, 2, 1, 0, 1, 2, 0, 2 };
float hC_values[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f };
float hC_result[] = { 70.0f, 80.0f, 90.0f,
184.0f,
246.0f, 288.0f, 330.0f,
334.0f, 450.0f };
float alpha = 1.0f;
float beta = 0.0f;
//--------------------------------------------------------------------------
// Device memory management
int *dC_offsets, *dC_columns;
float *dC_values, *dB, *dA;
CHECK_CUDA( cudaMalloc((void**) &dA, A_size * sizeof(float)) )
CHECK_CUDA( cudaMalloc((void**) &dB, B_size * sizeof(float)) )
CHECK_CUDA( cudaMalloc((void**) &dC_offsets,
(A_num_rows + 1) * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dC_columns, C_nnz * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dC_values, C_nnz * sizeof(float)) )
CHECK_CUDA( cudaMemcpy(dA, hA, A_size * sizeof(float),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dB, hB, B_size * sizeof(float),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dC_offsets, hC_offsets,
(A_num_rows + 1) * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dC_columns, hC_columns, C_nnz * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dC_values, hC_values, C_nnz * sizeof(float),
cudaMemcpyHostToDevice) )
//--------------------------------------------------------------------------
// CUSPARSE APIs
cusparseHandle_t handle = NULL;
cusparseDnMatDescr_t matA, matB;
cusparseSpMatDescr_t matC;
void* dBuffer = NULL;
size_t bufferSize = 0;
CHECK_CUSPARSE( cusparseCreate(&handle) )
// Create dense matrix A
CHECK_CUSPARSE( cusparseCreateDnMat(&matA, A_num_rows, A_num_cols, lda, dA,
CUDA_R_32F, CUSPARSE_ORDER_ROW) )
// Create dense matrix B
CHECK_CUSPARSE( cusparseCreateDnMat(&matB, A_num_cols, B_num_cols, ldb, dB,
CUDA_R_32F, CUSPARSE_ORDER_ROW) )
// Create sparse matrix C in CSR format
CHECK_CUSPARSE( cusparseCreateCsr(&matC, A_num_rows, B_num_cols, C_nnz,
dC_offsets, dC_columns, dC_values,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F) )
// allocate an external buffer if needed
CHECK_CUSPARSE( cusparseSDDMM_bufferSize(
handle,
CUSPARSE_OPERATION_NON_TRANSPOSE,
CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, matA, matB, &beta, matC, CUDA_R_32F,
CUSPARSE_SDDMM_ALG_DEFAULT, &bufferSize) )
CHECK_CUDA( cudaMalloc(&dBuffer, bufferSize) )
// execute preprocess (optional)
CHECK_CUSPARSE( cusparseSDDMM_preprocess(
handle,
CUSPARSE_OPERATION_NON_TRANSPOSE,
CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, matA, matB, &beta, matC, CUDA_R_32F,
CUSPARSE_SDDMM_ALG_DEFAULT, dBuffer) )
// execute SpMM
CHECK_CUSPARSE( cusparseSDDMM(handle,
CUSPARSE_OPERATION_NON_TRANSPOSE,
CUSPARSE_OPERATION_NON_TRANSPOSE,
&alpha, matA, matB, &beta, matC, CUDA_R_32F,
CUSPARSE_SDDMM_ALG_DEFAULT, dBuffer) )
// destroy matrix/vector descriptors
CHECK_CUSPARSE( cusparseDestroyDnMat(matA) )
CHECK_CUSPARSE( cusparseDestroyDnMat(matB) )
CHECK_CUSPARSE( cusparseDestroySpMat(matC) )
CHECK_CUSPARSE( cusparseDestroy(handle) )
//--------------------------------------------------------------------------
// device result check
CHECK_CUDA( cudaMemcpy(hC_values, dC_values, C_nnz * sizeof(float),
cudaMemcpyDeviceToHost) )
int correct = 1;
for (int i = 0; i < C_nnz; i++) {
if (hC_values[i] != hC_result[i]) {
correct = 0; // direct floating point comparison is not reliable
break;
}
}
if (correct)
printf("sddmm_csr_example test PASSED\n");
else
printf("sddmm_csr_example test FAILED: wrong result\n");
//--------------------------------------------------------------------------
// device memory deallocation
CHECK_CUDA( cudaFree(dBuffer) )
CHECK_CUDA( cudaFree(dA) )
CHECK_CUDA( cudaFree(dB) )
CHECK_CUDA( cudaFree(dC_offsets) )
CHECK_CUDA( cudaFree(dC_columns) )
CHECK_CUDA( cudaFree(dC_values) )
return EXIT_SUCCESS;
}