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dense2sparse_csr_example.c
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dense2sparse_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> // cusparseSparseToDense
#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 num_rows = 5;
int num_cols = 4;
int ld = num_cols;
int dense_size = ld * num_rows;
float h_dense[] = { 1.0f, 0.0f, 2.0f, 3.0f,
0.0f, 4.0f, 0.0f, 0.0f,
5.0f, 0.0f, 6.0f, 7.0f,
0.0f, 8.0f, 0.0f, 9.0f,
0.0f, 10.0f, 11.0f, 0.0f };
int h_csr_offsets[] = { 0, 0, 0, 0, 0, 0 };
int h_csr_columns[] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
float h_csr_values[] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
int h_csr_offsets_result[] = { 0, 3, 4, 7, 9, 11 };
int h_csr_columns_result[] = { 0, 2, 3, 1, 0, 2, 3, 1, 3, 1, 2 };
float h_csr_values_result[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f };
//--------------------------------------------------------------------------
// Device memory management
int *d_csr_offsets, *d_csr_columns;
float *d_csr_values, *d_dense;
CHECK_CUDA( cudaMalloc((void**) &d_dense, dense_size * sizeof(float)))
CHECK_CUDA( cudaMalloc((void**) &d_csr_offsets,
(num_rows + 1) * sizeof(int)) )
CHECK_CUDA( cudaMemcpy(d_dense, h_dense, dense_size * sizeof(float),
cudaMemcpyHostToDevice) )
//--------------------------------------------------------------------------
// CUSPARSE APIs
cusparseHandle_t handle = NULL;
cusparseSpMatDescr_t matB;
cusparseDnMatDescr_t matA;
void* dBuffer = NULL;
size_t bufferSize = 0;
CHECK_CUSPARSE( cusparseCreate(&handle) )
// Create dense matrix A
CHECK_CUSPARSE( cusparseCreateDnMat(&matA, num_rows, num_cols, ld, d_dense,
CUDA_R_32F, CUSPARSE_ORDER_ROW) )
// Create sparse matrix B in CSR format
CHECK_CUSPARSE( cusparseCreateCsr(&matB, num_rows, num_cols, 0,
d_csr_offsets, NULL, NULL,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F) )
// allocate an external buffer if needed
CHECK_CUSPARSE( cusparseDenseToSparse_bufferSize(
handle, matA, matB,
CUSPARSE_DENSETOSPARSE_ALG_DEFAULT,
&bufferSize) )
CHECK_CUDA( cudaMalloc(&dBuffer, bufferSize) )
// execute Sparse to Dense conversion
CHECK_CUSPARSE( cusparseDenseToSparse_analysis(handle, matA, matB,
CUSPARSE_DENSETOSPARSE_ALG_DEFAULT,
dBuffer) )
// get number of non-zero elements
int64_t num_rows_tmp, num_cols_tmp, nnz;
CHECK_CUSPARSE( cusparseSpMatGetSize(matB, &num_rows_tmp, &num_cols_tmp,
&nnz) )
// allocate CSR column indices and values
CHECK_CUDA( cudaMalloc((void**) &d_csr_columns, nnz * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &d_csr_values, nnz * sizeof(float)) )
// reset offsets, column indices, and values pointers
CHECK_CUSPARSE( cusparseCsrSetPointers(matB, d_csr_offsets, d_csr_columns,
d_csr_values) )
// execute Sparse to Dense conversion
CHECK_CUSPARSE( cusparseDenseToSparse_convert(handle, matA, matB,
CUSPARSE_DENSETOSPARSE_ALG_DEFAULT,
dBuffer) )
// destroy matrix/vector descriptors
CHECK_CUSPARSE( cusparseDestroyDnMat(matA) )
CHECK_CUSPARSE( cusparseDestroySpMat(matB) )
CHECK_CUSPARSE( cusparseDestroy(handle) )
//--------------------------------------------------------------------------
// device result check
CHECK_CUDA( cudaMemcpy(h_csr_offsets, d_csr_offsets,
(num_rows + 1) * sizeof(int),
cudaMemcpyDeviceToHost) )
CHECK_CUDA( cudaMemcpy(h_csr_columns, d_csr_columns, nnz * sizeof(int),
cudaMemcpyDeviceToHost) )
CHECK_CUDA( cudaMemcpy(h_csr_values, d_csr_values, nnz * sizeof(float),
cudaMemcpyDeviceToHost) )
int correct = 1;
for (int i = 0; i < num_rows + 1; i++) {
if (h_csr_offsets[i] != h_csr_offsets_result[i]) {
correct = 0;
break;
}
}
for (int i = 0; i < nnz; i++) {
if (h_csr_columns[i] != h_csr_columns_result[i]) {
correct = 0;
break;
}
}
for (int i = 0; i < nnz; i++) {
if (h_csr_values[i] != h_csr_values_result[i]) {
correct = 0;
break;
}
}
if (correct)
printf("dense2sparse_csr_example test PASSED\n");
else
printf("dense2sparse_csr_example test FAILED: wrong result\n");
//--------------------------------------------------------------------------
// device memory deallocation
CHECK_CUDA( cudaFree(dBuffer) )
CHECK_CUDA( cudaFree(d_csr_offsets) )
CHECK_CUDA( cudaFree(d_csr_columns) )
CHECK_CUDA( cudaFree(d_csr_values) )
CHECK_CUDA( cudaFree(d_dense) )
return EXIT_SUCCESS;
}