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spgemm_example.c
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spgemm_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> // cusparseSpGEMM
#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
#define A_NUM_ROWS 4 // C compatibility
const int A_num_rows = 4;
const int A_num_cols = 4;
const int A_nnz = 9;
const int B_num_rows = 4;
const int B_num_cols = 4;
const int B_nnz = 9;
int hA_csrOffsets[] = { 0, 3, 4, 7, 9 };
int hA_columns[] = { 0, 2, 3, 1, 0, 2, 3, 1, 3 };
float hA_values[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f,
6.0f, 7.0f, 8.0f, 9.0f };
int hB_csrOffsets[] = { 0, 2, 4, 7, 8 };
int hB_columns[] = { 0, 3, 1, 3, 0, 1, 2, 1 };
float hB_values[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f,
6.0f, 7.0f, 8.0f };
int hC_csrOffsets[] = { 0, 4, 6, 10, 12 };
int hC_columns[] = { 0, 1, 2, 3, 1, 3, 0, 1, 2, 3, 1, 3 };
float hC_values[] = { 11.0f, 36.0f, 14.0f, 2.0f, 12.0f,
16.0f, 35.0f, 92.0f, 42.0f, 10.0f,
96.0f, 32.0f };
const int C_nnz = 12;
#define C_NUM_NNZ 12 // C compatibility
float alpha = 1.0f;
float beta = 0.0f;
cusparseOperation_t opA = CUSPARSE_OPERATION_NON_TRANSPOSE;
cusparseOperation_t opB = CUSPARSE_OPERATION_NON_TRANSPOSE;
cudaDataType computeType = CUDA_R_32F;
//--------------------------------------------------------------------------
// Device memory management: Allocate and copy A, B
int *dA_csrOffsets, *dA_columns, *dB_csrOffsets, *dB_columns,
*dC_csrOffsets, *dC_columns;
float *dA_values, *dB_values, *dC_values;
// allocate A
CHECK_CUDA( cudaMalloc((void**) &dA_csrOffsets,
(A_num_rows + 1) * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dA_columns, A_nnz * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dA_values, A_nnz * sizeof(float)) )
// allocate B
CHECK_CUDA( cudaMalloc((void**) &dB_csrOffsets,
(B_num_rows + 1) * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dB_columns, B_nnz * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dB_values, B_nnz * sizeof(float)) )
// allocate C offsets
CHECK_CUDA( cudaMalloc((void**) &dC_csrOffsets,
(A_num_rows + 1) * sizeof(int)) )
// copy A
CHECK_CUDA( cudaMemcpy(dA_csrOffsets, hA_csrOffsets,
(A_num_rows + 1) * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dA_columns, hA_columns, A_nnz * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dA_values, hA_values,
A_nnz * sizeof(float), cudaMemcpyHostToDevice) )
// copy B
CHECK_CUDA( cudaMemcpy(dB_csrOffsets, hB_csrOffsets,
(B_num_rows + 1) * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dB_columns, hB_columns, B_nnz * sizeof(int),
cudaMemcpyHostToDevice) )
CHECK_CUDA( cudaMemcpy(dB_values, hB_values,
B_nnz * sizeof(float), cudaMemcpyHostToDevice) )
//--------------------------------------------------------------------------
// CUSPARSE APIs
cusparseHandle_t handle = NULL;
cusparseSpMatDescr_t matA, matB, matC;
void* dBuffer1 = NULL, *dBuffer2 = NULL;
size_t bufferSize1 = 0, bufferSize2 = 0;
CHECK_CUSPARSE( cusparseCreate(&handle) )
// Create sparse matrix A in CSR format
CHECK_CUSPARSE( cusparseCreateCsr(&matA, A_num_rows, A_num_cols, A_nnz,
dA_csrOffsets, dA_columns, dA_values,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F) )
CHECK_CUSPARSE( cusparseCreateCsr(&matB, B_num_rows, B_num_cols, B_nnz,
dB_csrOffsets, dB_columns, dB_values,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F) )
CHECK_CUSPARSE( cusparseCreateCsr(&matC, A_num_rows, B_num_cols, 0,
NULL, NULL, NULL,
CUSPARSE_INDEX_32I, CUSPARSE_INDEX_32I,
CUSPARSE_INDEX_BASE_ZERO, CUDA_R_32F) )
//--------------------------------------------------------------------------
// SpGEMM Computation
cusparseSpGEMMDescr_t spgemmDesc;
CHECK_CUSPARSE( cusparseSpGEMM_createDescr(&spgemmDesc) )
// ask bufferSize1 bytes for external memory
CHECK_CUSPARSE(
cusparseSpGEMM_workEstimation(handle, opA, opB,
&alpha, matA, matB, &beta, matC,
computeType, CUSPARSE_SPGEMM_DEFAULT,
spgemmDesc, &bufferSize1, NULL) )
CHECK_CUDA( cudaMalloc((void**) &dBuffer1, bufferSize1) )
// inspect the matrices A and B to understand the memory requirement for
// the next step
CHECK_CUSPARSE(
cusparseSpGEMM_workEstimation(handle, opA, opB,
&alpha, matA, matB, &beta, matC,
computeType, CUSPARSE_SPGEMM_DEFAULT,
spgemmDesc, &bufferSize1, dBuffer1) )
// ask bufferSize2 bytes for external memory
CHECK_CUSPARSE(
cusparseSpGEMM_compute(handle, opA, opB,
&alpha, matA, matB, &beta, matC,
computeType, CUSPARSE_SPGEMM_DEFAULT,
spgemmDesc, &bufferSize2, NULL) )
CHECK_CUDA( cudaMalloc((void**) &dBuffer2, bufferSize2) )
// compute the intermediate product of A * B
CHECK_CUSPARSE( cusparseSpGEMM_compute(handle, opA, opB,
&alpha, matA, matB, &beta, matC,
computeType, CUSPARSE_SPGEMM_DEFAULT,
spgemmDesc, &bufferSize2, dBuffer2) )
// get matrix C non-zero entries C_nnz1
int64_t C_num_rows1, C_num_cols1, C_nnz1;
CHECK_CUSPARSE( cusparseSpMatGetSize(matC, &C_num_rows1, &C_num_cols1,
&C_nnz1) )
// allocate matrix C
CHECK_CUDA( cudaMalloc((void**) &dC_columns, C_nnz1 * sizeof(int)) )
CHECK_CUDA( cudaMalloc((void**) &dC_values, C_nnz1 * sizeof(float)) )
// NOTE: if 'beta' != 0, the values of C must be update after the allocation
// of dC_values, and before the call of cusparseSpGEMM_copy
// update matC with the new pointers
CHECK_CUSPARSE(
cusparseCsrSetPointers(matC, dC_csrOffsets, dC_columns, dC_values) )
// if beta != 0, cusparseSpGEMM_copy reuses/updates the values of dC_values
// copy the final products to the matrix C
CHECK_CUSPARSE(
cusparseSpGEMM_copy(handle, opA, opB,
&alpha, matA, matB, &beta, matC,
computeType, CUSPARSE_SPGEMM_DEFAULT, spgemmDesc) )
// destroy matrix/vector descriptors
CHECK_CUSPARSE( cusparseSpGEMM_destroyDescr(spgemmDesc) )
CHECK_CUSPARSE( cusparseDestroySpMat(matA) )
CHECK_CUSPARSE( cusparseDestroySpMat(matB) )
CHECK_CUSPARSE( cusparseDestroySpMat(matC) )
CHECK_CUSPARSE( cusparseDestroy(handle) )
//--------------------------------------------------------------------------
// device result check
int hC_csrOffsets_tmp[A_NUM_ROWS + 1];
int hC_columns_tmp[C_NUM_NNZ];
float hC_values_tmp[C_NUM_NNZ];
CHECK_CUDA( cudaMemcpy(hC_csrOffsets_tmp, dC_csrOffsets,
(A_num_rows + 1) * sizeof(int),
cudaMemcpyDeviceToHost) )
CHECK_CUDA( cudaMemcpy(hC_columns_tmp, dC_columns, C_nnz * sizeof(int),
cudaMemcpyDeviceToHost) )
CHECK_CUDA( cudaMemcpy(hC_values_tmp, dC_values, C_nnz * sizeof(float),
cudaMemcpyDeviceToHost) )
int correct = 1;
for (int i = 0; i < A_num_rows + 1; i++) {
if (hC_csrOffsets_tmp[i] != hC_csrOffsets[i]) {
correct = 0;
break;
}
}
for (int i = 0; i < C_nnz; i++) {
if (hC_columns_tmp[i] != hC_columns[i] ||
hC_values_tmp[i] != hC_values[i]) { // direct floating point
correct = 0; // comparison is not reliable
break;
}
}
if (correct)
printf("spgemm_example test PASSED\n");
else {
printf("spgemm_example test FAILED: wrong result\n");
return EXIT_FAILURE;
}
//--------------------------------------------------------------------------
// device memory deallocation
CHECK_CUDA( cudaFree(dBuffer1) )
CHECK_CUDA( cudaFree(dBuffer2) )
CHECK_CUDA( cudaFree(dA_csrOffsets) )
CHECK_CUDA( cudaFree(dA_columns) )
CHECK_CUDA( cudaFree(dA_values) )
CHECK_CUDA( cudaFree(dB_csrOffsets) )
CHECK_CUDA( cudaFree(dB_columns) )
CHECK_CUDA( cudaFree(dB_values) )
CHECK_CUDA( cudaFree(dC_csrOffsets) )
CHECK_CUDA( cudaFree(dC_columns) )
CHECK_CUDA( cudaFree(dC_values) )
return EXIT_SUCCESS;
}