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#include <cusp/coo_matrix.h>
#include <cusp/csr_matrix.h>
#include <cusp/gallery/poisson.h>
#include <cusp/io/matrix_market.h>
#include <cusp/multiply.h>
#include <iostream>
#include <stdlib.h>
#include <stdio.h>
#include <cusparse_v2.h>
#include "../timer.h"
cusparseStatus_t status;
cusparseHandle_t handle = 0;
cusparseMatDescr_t descrA = 0;
cusparseMatDescr_t descrB = 0;
cusparseMatDescr_t descrC = 0;
#define CLEANUP(s) \
do { \
printf ("%s\n", s); \
if (descrA) cusparseDestroyMatDescr(descrA);\
if (descrB) cusparseDestroyMatDescr(descrB);\
if (descrC) cusparseDestroyMatDescr(descrC);\
if (handle) cusparseDestroy(handle); \
cudaDeviceReset(); \
fflush (stdout); \
} while (0)
int cusparse_init(void)
{
/* initialize cusparse library */
status = cusparseCreate(&handle);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("CUSPARSE Library initialization failed");
return 1;
}
/* create and setup matrix descriptor */
status = cusparseCreateMatDescr(&descrA);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix descriptor initialization failed");
return 1;
}
cusparseSetMatType(descrA,CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descrA,CUSPARSE_INDEX_BASE_ZERO);
status = cusparseCreateMatDescr(&descrB);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix descriptor initialization failed");
return 1;
}
cusparseSetMatType(descrB,CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descrB,CUSPARSE_INDEX_BASE_ZERO);
status = cusparseCreateMatDescr(&descrC);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix descriptor initialization failed");
return 1;
}
cusparseSetMatType(descrC,CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descrC,CUSPARSE_INDEX_BASE_ZERO);
return 0;
}
template <typename MatrixType, typename InputType>
float time_spmm(const InputType& A,
const InputType& B)
{
unsigned int N = 10;
MatrixType A_;
MatrixType B_;
try
{
A_ = A;
B_ = B;
}
catch (cusp::format_conversion_exception)
{
return -1;
}
timer t;
for(unsigned int i = 0; i < N; i++)
{
MatrixType C_;
cusp::multiply(A_, B_, C_);
}
return t.milliseconds_elapsed() / N;
}
template <typename MatrixType, typename InputType>
float time_cusparse(const InputType& A,
const InputType& B)
{
if( cusparse_init() )
{
throw cusp::runtime_exception("CUSPARSE init failed");
}
typedef typename MatrixType::index_type IndexType;
typedef typename MatrixType::value_type ValueType;
unsigned int N = 10;
int m = A.num_rows;
int n = A.num_cols;
int k = B.num_cols;
int nnzA = A.num_entries;
int nnzB = B.num_entries;
cusparseOperation_t transA = CUSPARSE_OPERATION_NON_TRANSPOSE;
cusparseOperation_t transB = CUSPARSE_OPERATION_NON_TRANSPOSE;
MatrixType A_(A);
MatrixType B_(B);
int * csrRowPtrA = thrust::raw_pointer_cast(&A_.row_offsets[0]);
int * csrColIndA = thrust::raw_pointer_cast(&A_.column_indices[0]);
float * csrValA = thrust::raw_pointer_cast(&A_.values[0]);
int * csrRowPtrB = thrust::raw_pointer_cast(&B_.row_offsets[0]);
int * csrColIndB = thrust::raw_pointer_cast(&B_.column_indices[0]);
float * csrValB = thrust::raw_pointer_cast(&B_.values[0]);
int * csrRowPtrC;
int * csrColIndC;
float * csrValC;
timer t;
for(unsigned int i = 0; i < N; i++)
{
int baseC, nnzC;
cudaMalloc((void**)&csrRowPtrC, sizeof(int)*(m+1));
status = cusparseXcsrgemmNnz(handle, transA, transB, m, n, k,
descrA, nnzA, csrRowPtrA, csrColIndA,
descrB, nnzB, csrRowPtrB, csrColIndB,
descrC, csrRowPtrC, &nnzC );
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("CSR Matrix-Matrix multiplication failed");
return 1;
}
cudaMemcpy(&nnzC , csrRowPtrC+m, sizeof(int), cudaMemcpyDeviceToHost);
cudaMemcpy(&baseC, csrRowPtrC , sizeof(int), cudaMemcpyDeviceToHost);
nnzC -= baseC;
cudaMalloc((void**)&csrColIndC, sizeof(int)*nnzC);
cudaMalloc((void**)&csrValC , sizeof(float)*nnzC);
status = cusparseScsrgemm(handle, transA, transB, m, n, k,
descrA, nnzA,
csrValA, csrRowPtrA, csrColIndA,
descrB, nnzB,
csrValB, csrRowPtrB, csrColIndB,
descrC,
csrValC, csrRowPtrC, csrColIndC);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("CSR Matrix-Matrix multiplication failed");
return 1;
}
cudaFree(csrRowPtrC);
cudaFree(csrColIndC);
cudaFree(csrValC);
}
return t.milliseconds_elapsed() / N;
}
int main(int argc, char ** argv)
{
typedef int IndexType;
typedef float ValueType;
typedef cusp::csr_matrix<IndexType,ValueType,cusp::host_memory> CSRHost;
typedef cusp::csr_matrix<IndexType,ValueType,cusp::device_memory> CSRDev;
typedef cusp::coo_matrix<IndexType,ValueType,cusp::device_memory> COO;
cudaSetDevice(0);
CSRHost A;
CSRHost B;
if (argc == 1)
{
// no input file was specified, generate an example
cusp::gallery::poisson5pt(A, 200, 200);
cusp::gallery::poisson5pt(B, 200, 200);
}
else if (argc == 2)
{
// no input file was specified, generate an example
cusp::io::read_matrix_market_file(A, argv[1]);
B = A;
}
else if (argc == 3)
{
// input files were specified, read them from disk
cusp::io::read_matrix_market_file(A, argv[1]);
cusp::io::read_matrix_market_file(B, argv[2]);
}
std::cout << "Input matrix A has shape (" << A.num_rows << "," << A.num_cols << ") and " << A.num_entries << " entries" << "\n";
std::cout << " B has shape (" << B.num_rows << "," << B.num_cols << ") and " << B.num_entries << " entries" << "\n\n";
printf("Host Sparse Matrix-Matrix Multiply (milliseconds per multiplication)\n");
printf(" Host | %9.2f\n", time_spmm<CSRHost>(A,B));
printf("\n\n");
printf("Device Sparse Matrix-Matrix Multiply (milliseconds per multiplication)\n");
printf(" Device | %9.2f\n", time_spmm<COO>(A,B));
printf(" CUSPARSE | %9.2f\n", time_cusparse<CSRDev>(A,B));
return 0;
}
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