VS2013+CUDA7.5
项目设置
1.新建cuda项目
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选择X64位，根据自己的需要定义Debug或Release模式
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2.项目属性-配置属性-VC++目录
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设置包含目录
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设置库目录
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3.项目属性-配置属性-链接器
常规－附加库目录：$(CUDA_PATH_V7.5)\lib$(Platform)
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输入－附加依赖项：
cublas.lib
cublas_device.lib
cuda.lib
cudadevrt.lib
cudart.lib
cudart_static.lib
cufft.lib
cufftw.lib
curand.lib
cusolver.lib
cusparse.lib
nppc.lib
nppi.lib
npps.lib
nvblas.lib
nvcuvid.lib
nvrtc.lib
OpenCL.lib
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4.设置windows调制器为X64位
由于cusparse.lib是X64位下的库，所以要设置成X64运行模式，如果不设置就会出现如下的错误。
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修改：
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实验结果：
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#include<stdio.h>
#include<stdlib.h>
#include<cuda_runtime.h>
#include"cusparse.h"
#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)
int main(){
cudaError_t cudaStat1, cudaStat2, cudaStat3, cudaStat4, cudaStat5, cudaStat6;
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;
double * cooVal = 0;
int * xIndHostPtr = 0;
double * xValHostPtr = 0;
double * yHostPtr = 0;
int * xInd = 0;
double * xVal = 0;
double * y = 0;
int * csrRowPtr = 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;
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;
//*
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]);
}
//*/
/* create a sparse and dense vector */
/*
xVal= [100.0 200.0 400.0] (sparse)
xInd= [0 1 3 ]
y = [10.0 20.0 30.0 40.0 | 50.0 60.0 70.0 80.0] (dense)
*/
nnz_vector = 3;
xIndHostPtr = (int *)malloc(nnz_vector*sizeof(xIndHostPtr[0]));
xValHostPtr = (double *)malloc(nnz_vector*sizeof(xValHostPtr[0]));
yHostPtr = (double *)malloc(2 * n*sizeof(yHostPtr[0]));
zHostPtr = (double *)malloc(2 * (n + 1)*sizeof(zHostPtr[0]));
if ((!xIndHostPtr) || (!xValHostPtr) || (!yHostPtr) || (!zHostPtr)){
CLEANUP("Host malloc failed (vectors)");
return 1;
}
yHostPtr[0] = 10.0; xIndHostPtr[0] = 0; xValHostPtr[0] = 100.0;
yHostPtr[1] = 20.0; xIndHostPtr[1] = 1; xValHostPtr[1] = 200.0;
yHostPtr[2] = 30.0;
yHostPtr[3] = 40.0; xIndHostPtr[2] = 3; xValHostPtr[2] = 400.0;
yHostPtr[4] = 50.0;
yHostPtr[5] = 60.0;
yHostPtr[6] = 70.0;
yHostPtr[7] = 80.0;
//printf the vectors
for (int j = 0; j < 2; j++){
for (int i = 0; i < n; i++){
printf("yHostPtr[%d,%d]=%f\n", i, j, yHostPtr[i + n*j]);
}
}
for (int i = 0; i < nnz_vector; i++){
printf("xIndHostPtr[%d]=%d ", i, xIndHostPtr[i]);
printf("xValHostPtr[%d]=%f\n", i, xValHostPtr[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]));
cudaStat4 = cudaMalloc((void**)&y, 2 * n*sizeof(y[0]));
cudaStat5 = cudaMalloc((void**)&xInd, nnz_vector*sizeof(xInd[0]));
cudaStat6 = cudaMalloc((void**)&xVal, nnz_vector*sizeof(xVal[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(cooColIndexHostPtr[0])),
cudaMemcpyHostToDevice);
cudaStat3 = cudaMemcpy(cooVal, cooValHostPtr,
(size_t)(nnz*sizeof(cooValHostPtr[0])),
cudaMemcpyHostToDevice);
cudaStat4 = cudaMemcpy(y, yHostPtr,
(size_t)(2 * n*sizeof(y[0])),
cudaMemcpyHostToDevice);
cudaStat5 = cudaMemcpy(xInd, xIndHostPtr,
(size_t)(nnz_vector*sizeof(xInd[0])),
cudaMemcpyHostToDevice);
cudaStat6 = cudaMemcpy(xVal, xValHostPtr,
(size_t)(nnz_vector*sizeof(xVal[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((void**)&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;
}
//csrRowPtr = [0 3 4 7 9]
// The following test only works for compute capability 1.3 and above
// because it needs double precision.
int devId;
cudaDeviceProp prop; //cudaDeviceProp</strong>数据类型针对函式 <strong>cudaGetDeviceProperties</strong>定义的，<strong>cudaGetDeviceProperties</strong>函数的功能是取得支持GPU计算的装置的相关属性，如支持CUDA版本号装置的名称、内存的大小、最大的 thread 数目、执行单元的频率
cudaError_t cudaStat;
cudaStat = cudaGetDevice(&devId);
if (cudaStat != cudaSuccess){
CLEANUP("cudaGetDevice failed");
printf("Error: cudaStat %d, %s\n", cudaStat, cudaGetErrorString(cudaStat));
return 1;
}
cudaStat = cudaGetDeviceProperties(&prop, devId);
if (cudaStat != cudaSuccess){
CLEANUP("cudaGetDeviceProperties failed");
printf("Error: cudaStat %d, %s\n", cudaStat, cudaGetErrorString(cudaStat));
return 1;
}
int cc = 100 * prop.major + 10 * prop.minor; //major计算能力的主代号,minor计算能力的次要代号
if (cc < 130){
CLEANUP("waive the test because only sm13 and above are supported\n");
printf("the device has compute capability %d\n", cc);
printf("example test WAIVED");
return 2;
}
/* exercise Level 1 routines (scatter vector elements) */
status = cusparseDsctr(handle, nnz_vector, xVal, xInd,
&y[n], CUSPARSE_INDEX_BASE_ZERO);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Scatter from sparse to dense vector failed");
return 1;
}
//y = [10 20 30 40 | 100 200 70 400]
/* exercise Level 2 routines (csrmv) */
status = cusparseDcsrmv(handle, CUSPARSE_OPERATION_NON_TRANSPOSE, n, n, nnz,
&dtwo, descr, cooVal, csrRowPtr, cooColIndex,
&y[0], &dthree, &y[n]);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix-vector multiplication failed");
return 1;
}
//y = [10 20 30 40 | 680 760 1230 2240]
cudaMemcpy(yHostPtr, y, (size_t)(2 * n*sizeof(y[0])), cudaMemcpyDeviceToHost);
printf("Intermediate results:\n");
for (int j = 0; j < 2; j++){
for (int i = 0; i < n; i++){
printf("yHostPtr[%d,%d]=%f\n", i, j, yHostPtr[i + n*j]);
}
}
/* exercise Level 3 routines (csrmm) */
cudaStat1 = cudaMalloc((void**)&z, 2 * (n + 1)*sizeof(z[0]));
if (cudaStat1 != cudaSuccess) {
CLEANUP("Device malloc failed(z)");
return 1;
}
cudaStat1 = cudaMemset((void *)z, 0, 2 * (n + 1)*sizeof(z[0]));
if (cudaStat1 != cudaSuccess) {
CLEANUP("Memset on Device failed");
return 1;
}
status = cusparseDcsrmm(handle, CUSPARSE_OPERATION_NON_TRANSPOSE, n, 2, n, nnz,
&dfive, descr, cooVal, csrRowPtr, cooColIndex,
y, n, &dzero, z, n + 1);
if (status != CUSPARSE_STATUS_SUCCESS) {
CLEANUP("Matrix-matrix multiplication failed");
return 1;
}
//z = [950 400 2550 2600 0 | 49300 15200 132300 131200 0]
/* print final results (z) */
cudaStat1 = cudaMemcpy(zHostPtr, z,
(size_t)(2 * (n + 1)*sizeof(z[0])),
cudaMemcpyDeviceToHost);
if (cudaStat1 != cudaSuccess) {
CLEANUP("Memcpy from Device to Host failed");
return 1;
}
printf("Final results:\n");
for (int j = 0; j < 2; j++){
for (int i = 0; i < n + 1; i++){
printf("z[%d,%d]=%f\n", i, j, zHostPtr[i + (n + 1)*j]);
}
}
/* 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;
}
/* check the results */
/* Notice that CLEANUP() contains a call to cusparseDestroy(handle) */
if ((zHostPtr[0] != 950.0) ||
(zHostPtr[1] != 400.0) ||
(zHostPtr[2] != 2550.0) ||
(zHostPtr[3] != 2600.0) ||
(zHostPtr[4] != 0.0) ||
(zHostPtr[5] != 49300.0) ||
(zHostPtr[6] != 15200.0) ||
(zHostPtr[7] != 132300.0) ||
(zHostPtr[8] != 131200.0) ||
(zHostPtr[9] != 0.0) ||
(yHostPtr[0] != 10.0) ||
(yHostPtr[1] != 20.0) ||
(yHostPtr[2] != 30.0) ||
(yHostPtr[3] != 40.0) ||
(yHostPtr[4] != 680.0) ||
(yHostPtr[5] != 760.0) ||
(yHostPtr[6] != 1230.0) ||
(yHostPtr[7] != 2240.0)){
CLEANUP("example test FAILED");
return 1;
}
else{
CLEANUP("example test PASSED");
//return 0;
}
getchar();
}
