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sparse2dense_csr_example.c
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140 lines (134 loc) · 6.84 KB
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/*
* SPDX-FileCopyrightText: Copyright (c) 1993-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#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 nnz = 11;
int ld = num_cols;
int dense_size = ld * num_rows;
int h_csr_offsets[] = { 0, 3, 4, 7, 9, 11 };
int h_csr_columns[] = { 0, 2, 3, 1, 0, 2, 3, 1, 3, 1, 2 };
float h_csr_values[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f };
float h_dense[] = { 0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 0.0f };
float h_dense_result[] = { 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 };
//--------------------------------------------------------------------------
// Device memory management
int *d_csr_offsets, *d_csr_columns;
float *d_csr_values, *d_dense;
CHECK_CUDA( cudaMalloc((void**) &d_csr_offsets,
(num_rows + 1) * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &d_csr_columns, nnz * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &d_csr_values, nnz * sizeof(float)) )
CHECK_CUDA( cudaMalloc((void**) &d_dense, dense_size * sizeof(float)))
CHECK_CUDA( cudaMemcpy(d_csr_offsets, h_csr_offsets,
(num_rows + 1) * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(d_csr_columns, h_csr_columns, nnz * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(d_csr_values, h_csr_values, nnz * sizeof(float),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(d_dense, h_dense, dense_size * sizeof(float),
cudaMemcpyHostToDevice) )
//--------------------------------------------------------------------------
// CUSPARSE APIs
cusparseHandle_t handle = NULL;
cusparseSpMatDescr_t matA;
cusparseDnMatDescr_t matB;
void* dBuffer = NULL;
size_t bufferSize = 0;
CHECK_CUSPARSE( cusparseCreate(&handle) )
// Create sparse matrix A in CSR format
CHECK_CUSPARSE( cusparseCreateCsr(&matA, num_rows, num_cols, nnz,
d_csr_offsets, d_csr_columns,
d_csr_values, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F) )
// Create dense matrix B
CHECK_CUSPARSE( cusparseCreateDnMat(&matB, num_rows, num_cols, ld, d_dense,
CUDA_R_32F, CUSPARSE_ORDER_ROW) )
// allocate an external buffer if needed
CHECK_CUSPARSE( cusparseSparseToDense_bufferSize(
handle, matA, matB,
CUSPARSE_SPARSETODENSE_ALG_DEFAULT,
&bufferSize) )
CHECK_CUDA( cudaMalloc(&dBuffer, bufferSize) )
// execute Sparse to Dense conversion
CHECK_CUSPARSE( cusparseSparseToDense(handle, matA, matB,
CUSPARSE_SPARSETODENSE_ALG_DEFAULT,
dBuffer) )
// destroy matrix/vector descriptors
CHECK_CUSPARSE( cusparseDestroySpMat(matA) )
CHECK_CUSPARSE( cusparseDestroyDnMat(matB) )
CHECK_CUSPARSE( cusparseDestroy(handle) )
//--------------------------------------------------------------------------
// device result check
CHECK_CUDA( cudaMemcpy(h_dense, d_dense, dense_size * sizeof(float),
cudaMemcpyDeviceToHost) )
int correct = 1;
for (int i = 0; i < num_rows; i++) {
for (int j = 0; j < num_cols; j++) {
if (h_dense[i * ld + j] != h_dense_result[i * ld + j]) {
correct = 0;
break;
}
}
}
if (correct)
printf("sparse2dense_example test PASSED\n");
else
printf("sparse2dense_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;
}