【发布时间】：2023-03-06 23:53:01
【问题描述】：
我正在尝试使用 cuSPARSE 库实现稀疏矩阵乘法。我使用了文档中的大部分代码，即来自here。 即使我得到了正确的行指针、输出的列指针，我得到的输出值也不正确。
我已按照以下步骤操作： 1.生成coo格式矩阵。 2.转换成csr格式 3. 求非零元素向量以及输出矩阵中非零元素的个数 4. 执行矩阵乘法 5. 打印结果
除了输出矩阵值，我得到了正确的结果（行指针、列指针是正确的）——同样可以通过执行下面的代码来打印。我知道我错过了一些简单的东西，但我无法弄清楚。请让我知道出了什么问题以及如何纠正。
#include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>
#include "cusparse_v2.h"
#include <cuda_runtime_api.h>
#include<iostream>
#include<iomanip>
#include<assert.h>
#include <time.h>
#include <sys/time.h>
#define CUSPARSE_CHECK(x) {cusparseStatus_t _c=x; if (_c != CUSPARSE_STATUS_SUCCESS) {printf("cusparse fail: %d, line: %d\n", (int)_c, __LINE__); if(_c == CUSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED) {printf("CUSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED\n");} if(_c == CUSPARSE_STATUS_INTERNAL_ERROR) {printf("CUSPARSE_STATUS_INTERNAL_ERROR\n");} exit(-1);}}
#define CLEANUP(s) \
do { \
printf ("%s\n", s); \
if (yHostPtr) free(yHostPtr); \
if (zHostPtr) free(zHostPtr); \
if (xIndHostPtr) free(xIndHostPtr); \
if (xValHostPtr) free(xValHostPtr); \
if (cooRowIndexHostPtr) free(cooRowIndexHostPtr);\
if (cooColIndexHostPtr) free(cooColIndexHostPtr);\
if (cooValHostPtr) free(cooValHostPtr); \
if (y) cudaFree(y); \
if (z) cudaFree(z); \
if (xInd) cudaFree(xInd); \
if (xVal) cudaFree(xVal); \
if (csrRowPtr) cudaFree(csrRowPtr); \
if (cooRowIndex) cudaFree(cooRowIndex); \
if (cooColIndex) cudaFree(cooColIndex); \
if (cooVal) cudaFree(cooVal); \
if (descr) cusparseDestroyMatDescr(descr);\
if (handle) cusparseDestroy(handle); \
cudaDeviceReset(); \
fflush (stdout); \
} while (0)
double timerval()
{
struct timeval st;
gettimeofday(&st, NULL);
return (st.tv_sec+st.tv_usec*1e-6);
}
int main(){
cudaError_t cudaStat1 = cudaSuccess,cudaStat2 = cudaSuccess,cudaStat3 = cudaSuccess,cudaStat4 = cudaSuccess,cudaStat5 = cudaSuccess,cudaStat6 = cudaSuccess;
cusparseStatus_t status;
cusparseHandle_t handle=0;
cusparseMatDescr_t descr=0;
int * cooRowIndexHostPtr=0;
int * cooColIndexHostPtr=0;
double * cooValHostPtr=0;
int * cooRowIndex=0;
int * cooColIndex=0;
float * cooVal=0;
int * xIndHostPtr=0;
double * xValHostPtr=0;
double * yHostPtr=0;
int * xInd=0;
double * xVal=0;
double * y=0;
int * csrRowPtr=0;
int * csrColPtr = 0;
double * zHostPtr=0;
double * z=0;
int n, nnz, nnz_vector;
double dzero =0.0;
double dtwo =2.0;
double dthree=3.0;
double dfive =5.0;
cusparseStatus_t stat;
double avg_time = 0, s_time, e_time;
cusparseMatDescr_t descrA, descrB, descrC;
stat = cusparseCreateMatDescr(&descrA);
CUSPARSE_CHECK(stat);
stat = cusparseCreateMatDescr(&descrB);
CUSPARSE_CHECK(stat);
stat = cusparseCreateMatDescr(&descrC);
CUSPARSE_CHECK(stat);
stat = cusparseSetMatType(descrA, CUSPARSE_MATRIX_TYPE_GENERAL);
CUSPARSE_CHECK(stat);
stat = cusparseSetMatType(descrB, CUSPARSE_MATRIX_TYPE_GENERAL);
CUSPARSE_CHECK(stat);
stat = cusparseSetMatType(descrC, CUSPARSE_MATRIX_TYPE_GENERAL);
CUSPARSE_CHECK(stat);
stat = cusparseSetMatIndexBase(descrA, CUSPARSE_INDEX_BASE_ZERO);
CUSPARSE_CHECK(stat);
stat = cusparseSetMatIndexBase(descrB, CUSPARSE_INDEX_BASE_ZERO);
CUSPARSE_CHECK(stat);
stat = cusparseSetMatIndexBase(descrC, CUSPARSE_INDEX_BASE_ZERO);
CUSPARSE_CHECK(stat);
printf("testing example\n");
/* create the following sparse test matrix in COO format */
/* |1.0 2.0 3.0|
| 4.0 |
|5.0 6.0 7.0|
| 8.0 9.0| */
n=4; nnz=9;
cooRowIndexHostPtr = (int *) malloc(nnz*sizeof(cooRowIndexHostPtr[0]));
cooColIndexHostPtr = (int *) malloc(nnz*sizeof(cooColIndexHostPtr[0]));
cooValHostPtr = (double *)malloc(nnz*sizeof(cooValHostPtr[0]));
if ((!cooRowIndexHostPtr) || (!cooColIndexHostPtr) || (!cooValHostPtr)){
CLEANUP("Host malloc failed (matrix)");
return 1;
}
cooRowIndexHostPtr[0]=0; cooColIndexHostPtr[0]=0; cooValHostPtr[0]=1.0;
cooRowIndexHostPtr[1]=0; cooColIndexHostPtr[1]=2; cooValHostPtr[1]=2.0;
cooRowIndexHostPtr[2]=0; cooColIndexHostPtr[2]=3; cooValHostPtr[2]=3.0;
cooRowIndexHostPtr[3]=1; cooColIndexHostPtr[3]=1; cooValHostPtr[3]=4.0;
cooRowIndexHostPtr[4]=2; cooColIndexHostPtr[4]=0; cooValHostPtr[4]=5.0;
cooRowIndexHostPtr[5]=2; cooColIndexHostPtr[5]=2; cooValHostPtr[5]=6.0;
cooRowIndexHostPtr[6]=2; cooColIndexHostPtr[6]=3; cooValHostPtr[6]=7.0;
cooRowIndexHostPtr[7]=3; cooColIndexHostPtr[7]=1; cooValHostPtr[7]=8.0;
cooRowIndexHostPtr[8]=3; cooColIndexHostPtr[8]=3; cooValHostPtr[8]=9.0;
//print the matrix
printf("Input data:\n");
for (int i=0; i<nnz; i++){
printf("cooRowIndexHostPtr[%d]=%d ",i,cooRowIndexHostPtr[i]);
printf("cooColIndexHostPtr[%d]=%d ",i,cooColIndexHostPtr[i]);
printf("cooValHostPtr[%d]=%f \n",i,cooValHostPtr[i]);
}
/* allocate GPU memory and copy the matrix and vectors into it */
cudaStat1 = cudaMalloc((void**)&cooRowIndex,nnz*sizeof(cooRowIndex[0]));
cudaStat2 = cudaMalloc((void**)&cooColIndex,nnz*sizeof(cooColIndex[0]));
cudaStat3 = cudaMalloc((void**)&cooVal, nnz*sizeof(cooVal[0]));
if ((cudaStat1 != cudaSuccess) ||
(cudaStat2 != cudaSuccess) ||
(cudaStat3 != cudaSuccess) ||
(cudaStat4 != cudaSuccess) ||
(cudaStat5 != cudaSuccess) ||
(cudaStat6 != cudaSuccess)) {
CLEANUP("Device malloc failed");
return 1;
}
cudaStat1 = cudaMemcpy(cooRowIndex, cooRowIndexHostPtr,
(size_t)(nnz*sizeof(cooRowIndex[0])),
cudaMemcpyHostToDevice);
cudaStat2 = cudaMemcpy(cooColIndex, cooColIndexHostPtr,
(size_t)(nnz*sizeof(cooColIndex[0])),
cudaMemcpyHostToDevice);
cudaStat3 = cudaMemcpy(cooVal, cooValHostPtr,
(size_t)(nnz*sizeof(cooVal[0])),
cudaMemcpyHostToDevice);
if ((cudaStat1 != cudaSuccess) ||
(cudaStat2 != cudaSuccess) ||
(cudaStat3 != cudaSuccess) ||
(cudaStat4 != cudaSuccess) ||
(cudaStat5 != cudaSuccess) ||
(cudaStat6 != cudaSuccess)) {
CLEANUP("Memcpy from Host to Device failed");
return 1;
}
/* 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(&descr);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix descriptor initialization failed");
return 1;
}
cusparseSetMatType(descr,CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descr,CUSPARSE_INDEX_BASE_ZERO);
/* exercise conversion routines (convert matrix from COO 2 CSR format) */
cudaStat1 = cudaMalloc(&csrRowPtr,(n+1)*sizeof(csrRowPtr[0]));
if (cudaStat1 != cudaSuccess) {
CLEANUP("Device malloc failed (csrRowPtr)");
return 1;
}
status= cusparseXcoo2csr(handle,cooRowIndex,nnz,n,
csrRowPtr,CUSPARSE_INDEX_BASE_ZERO);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Conversion from COO to CSR format failed");
return 1;
}
/*
int *csr_values;
csr_values = (int *)malloc((n+1)*sizeof(int));
cudaStat3 = cudaMemcpy(csr_values, csrRowPtr, (n+1)*sizeof(int), cudaMemcpyDeviceToHost);
if (cudaStat3 != cudaSuccess) {
CLEANUP("Device memcopy failed: csr values");
return 1;
}
printf("CSR values are \n");
for(int y2 =0; y2< n+1; y2++)
printf("%d \t", csr_values[y2]);
*/
/*
int y1;
printf("\n");
printf("col orig is\n");
for(y1 =0; y1 < nnz; y1++)
{
printf("%d\t", cooColIndex[y1]);
}
printf("\n");
printf("nnz orig is\n");
for(y1 =0; y1 < nnz; y1++)
{
printf("%f\t", h_csrValC[y1]);
}
*/
//csrRowPtr data is present now
//csrRowPtr, cooColIndex, cooVal (all the three are matrix A data) shall be used from here for the operation
int nnzA = nnz, nnzB = nnz, nnzC;
cusparseOperation_t transA = CUSPARSE_OPERATION_NON_TRANSPOSE;
cusparseOperation_t transB = CUSPARSE_OPERATION_NON_TRANSPOSE;
// figure out size of C
int baseC;
int *csrRowPtrC, *csrColIndC;
float *csrValC;
// nnzTotalDevHostPtr points to host memory
int *nnzTotalDevHostPtr = &nnzC;
stat = cusparseSetPointerMode(handle, CUSPARSE_POINTER_MODE_HOST);
CUSPARSE_CHECK(stat);
cudaStat1 = cudaMalloc((void**)&csrRowPtrC, sizeof(int)*(n+1));
if (cudaStat1 != cudaSuccess) {
CLEANUP("Device malloc failed (csrRowPtr)");
return 1;
}
s_time=timerval();
//from here add code to multiply
/*
*/
stat = cusparseXcsrgemmNnz(handle, transA, transB, n, n, n,
descrA, nnzA, csrRowPtr, cooColIndex /*csrColInd*/,
descrB, nnzB, csrRowPtr, cooColIndex /*csrColInd*/,
descrC, csrRowPtrC, nnzTotalDevHostPtr );
CUSPARSE_CHECK(stat);
if (NULL != nnzTotalDevHostPtr)
{
nnzC = *nnzTotalDevHostPtr;
}
else{
cudaStat1 = cudaMemcpy(&nnzC, csrRowPtrC+n, sizeof(int), cudaMemcpyDeviceToHost);
cudaStat2 = cudaMemcpy(&baseC, csrRowPtrC, sizeof(int), cudaMemcpyDeviceToHost);
if (cudaStat1 || cudaStat2 != cudaSuccess) {
CLEANUP("Device malloc failed (csrRowPtr)");
return 1;
}
nnzC -= baseC;}
cudaStat1 = cudaMalloc((void**)&csrColIndC, sizeof(int)*nnzC);
if (cudaStat1 != cudaSuccess) {
CLEANUP("Device malloc failed (csrColIndC)");
return 1;
}
cudaStat1 = cudaMalloc((void**)&csrValC, sizeof(float)*nnzC);
if (cudaStat1 != cudaSuccess) {
CLEANUP("Device malloc failed (csrValC)");
return 1;
}
stat = cusparseScsrgemm(handle, transA, transB, n, n, n,
descrA, nnzA,
cooVal/*csrValA*/, csrRowPtr, cooColIndex,
descrB, nnzB,
cooVal/*csrValA*/, csrRowPtr, cooColIndex,
descrC,
csrValC/*csrValA*/, csrRowPtrC, csrColIndC);
CUSPARSE_CHECK(stat);
cudaDeviceSynchronize();
int *h_csrRowPtrC = NULL, *h_csrColIndC = NULL;
float *h_csrValC = NULL;
h_csrValC = (float *)malloc(nnzC*sizeof(float));
h_csrRowPtrC = (int *)malloc(n+1*sizeof(int));
h_csrColIndC = (int *)malloc(nnzC*sizeof(int));
cudaStat1 = cudaMemcpy(h_csrRowPtrC, csrRowPtrC, (n+1)*sizeof(int), cudaMemcpyDeviceToHost);
if (cudaStat1 != cudaSuccess) {
CLEANUP("Device memcopy failed csrRowPtrC");
return 1;
}
cudaStat2 = cudaMemcpy(h_csrColIndC, csrColIndC, nnzC*sizeof(int), cudaMemcpyDeviceToHost);
if (cudaStat2 != cudaSuccess) {
CLEANUP("Device memcopy failed: cooColIndex");
return 1;
}
printf("nnz value is %d, nnzc is %d\n", nnz, nnzC);
cudaStat3 = cudaMemcpy(h_csrValC, csrValC, nnzC*sizeof(float), cudaMemcpyDeviceToHost);
if (cudaStat3 != cudaSuccess) {
CLEANUP("Device memcopy failed: csrValC");
return 1;
}
int y1;
printf("row is\n");
for(y1 =0; y1 < n+1; y1++)
{
printf("%d\t", h_csrRowPtrC[y1]);
}
printf("\n");
printf("col is\n");
for(y1 =0; y1 < nnzC; y1++)
{
printf("%d\t", h_csrColIndC[y1]);
}
printf("\n");
printf("nnz is\n");
for(y1 =0; y1 < nnzC; y1++)
{
printf("%f\t", h_csrValC[y1]);
}
/* destroy matrix descriptor */
status = cusparseDestroyMatDescr(descr);
descr = 0;
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix descriptor destruction failed");
return 1;
}
/* destroy handle */
status = cusparseDestroy(handle);
handle = 0;
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("CUSPARSE Library release of resources failed");
return 1;
}
cudaFree(csrRowPtr);
cudaFree(cooColIndex);
cudaFree(cooRowIndex);
cudaFree(cooVal);
cudaFree(csrRowPtrC);
cudaFree(csrColIndC);
cudaFree(csrValC);
return 0;
}
【问题讨论】：
标签： cuda nvidia sparse-matrix gpu cusp-library