我正在测试一些场景,在这些场景中,与为dgetrf
编写函数相比,与cuBLAS/cuSOLVER
一起使用时,函数LAPACK
的返回方式有所不同。例如,我正在研究以下矩阵的LU分解:
2.0 4.0 1.0 -3.0 0.0 -1.0 -2.0 2.0 4.0 0.0 4.0 2.0 -3.0 5.0 0.0 5.0 -4.0 -3.0 1.0 0.0 0.0 0.0 0.0
我首先尝试按下面的方式从dgetrf
调用cuBLAS/cuSOLVER
(前面是警告、丑陋的测试代码!)
#include <cblas.h>
#include <time.h>
#include <stdio.h>
#include <string.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cusolverDn.h>
int main(int argc, char** argv){
const int matrixSize = 5;
int i, j;
double arrA[matrixSize][matrixSize] = {
{2.0, 4.0, 1.0, -3.0, 0.0},
{-1.0, -2.0, 2.0, 4.0, 0.0},
{4.0, 2.0, -3.0, 5.0, 0.0},
{5.0, -4.0, -3.0, 1.0, 0.0},
{0.0, 0.0, 0.0, 0.0, 0.0}
};
double *arrADev, *workArray;
double **matrixArray;
int *pivotArray;
int *infoArray;
double flat[matrixSize*matrixSize] = {0};
cublasHandle_t cublasHandle;
cublasStatus_t cublasStatus;
cudaError_t error;
cudaError cudaStatus;
cusolverStatus_t cusolverStatus;
cusolverDnHandle_t cusolverHandle;
double *matrices[2];
error = cudaMalloc(&arrADev, sizeof(double) * matrixSize*matrixSize);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
error = cudaMalloc(&matrixArray, sizeof(double*) * 2);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
error = cudaMalloc(&pivotArray, sizeof(int) * matrixSize*matrixSize);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
error = cudaMalloc(&infoArray, sizeof(int) * matrixSize*matrixSize);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
cublasStatus = cublasCreate(&cublasHandle);
if (cublasStatus != CUBLAS_STATUS_SUCCESS) fprintf(stderr,"error %i\n",cublasStatus);
//maps matrix to flat vector
for(i=0; i<matrixSize; i++){
for(j=0; j<matrixSize; j++){
flat[i+j*matrixSize] = arrA[i][j];
}
}
//copy matrix A to device
cublasStatus = cublasSetMatrix(matrixSize, matrixSize, sizeof(double), flat, matrixSize, arrADev, matrixSize);
if (cublasStatus != CUBLAS_STATUS_SUCCESS) fprintf(stderr,"error %i\n",cublasStatus);
//save matrix address
matrices[0] = arrADev;
//copy matrices references to device
error = cudaMemcpy(matrixArray, matrices, sizeof(double*)*1, cudaMemcpyHostToDevice);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
int Lwork;
// calculate buffer size for cuSOLVER LU factorization
cusolverStatus = cusolverDnDgetrf_bufferSize(cusolverHandle, matrixSize, matrixSize, arrADev, matrixSize, &Lwork);
cudaStatus = cudaMalloc((void**)&workArray, Lwork*sizeof(double));
// cuBLAS LU factorization
cublasStatus = cublasDgetrfBatched(cublasHandle, matrixSize, matrixArray, matrixSize, pivotArray, infoArray, 1);
if (cublasStatus == CUBLAS_STATUS_SUCCESS)
printf("cuBLAS DGETRF SUCCESSFUL! \n");
else
printf("cuBLAS DGETRF UNSUCCESSFUL! \n");
// cuSOLVER LU factorization
cusolverStatus = cusolverDnCreate(&cusolverHandle);
cusolverStatus = cusolverDnDgetrf(cusolverHandle, matrixSize, matrixSize, arrADev, matrixSize, workArray, pivotArray, infoArray);
if (cusolverStatus == CUSOLVER_STATUS_SUCCESS)
printf("cuSOLVER DGETRF SUCCESSFUL! \n");
else
printf("cuSOLVER DGETRF UNSUCCESSFUL! \n");
return 0;
}
上面代码的输出是
cuBLAS DGETRF SUCCESSFUL!
cuSOLVER DGETRF SUCCESSFUL!
当我试图对LAPACK做同样的事情时(警告:更丑陋的代码!):
#include <iostream>
#include <vector>
using namespace std;
extern "C" void dgetrf_(int* dim1, int* dim2, double* a, int* lda, int* ipiv, int* info);
extern "C" void dgetrs_(char *TRANS, int *N, int *NRHS, double *A, int *LDA, int *IPIV, double *B, int *LDB, int *INFO );
int main()
{
char trans = 'N';
int dim = 5;
int LDA = dim;
int info;
vector<double> a,b;
a.push_back(2.0); a.push_back(4.0); a.push_back(1.0); a.push_back(-3.0); a.push_back(0.0);
a.push_back(-1.0); a.push_back(-2.0); a.push_back(2.0); a.push_back(4.0); a.push_back(0.0);
a.push_back(4.0); a.push_back(2.0); a.push_back(-3.0); a.push_back(5.0); a.push_back(0.0);
a.push_back(5.0); a.push_back(-4.0); a.push_back(-3.0); a.push_back(1.0); a.push_back(0.0);
a.push_back(0.0); a.push_back(0.0); a.push_back(0.0); a.push_back(0.0); a.push_back(0.0);
int ipiv[5];
dgetrf_(&dim, &dim, &*a.begin(), &LDA, ipiv, &info);
if (info == 0)
printf("dgetrf successful\n");
else
printf("dgetrf unsuccessful\n");
return 0;
}
我得到的输出是
dgetrf unsuccessful
我知道他们是不同的图书馆,但这种行为是否被期望?
发布于 2019-11-11 15:48:18
当我编译您的CUDA代码时,会收到一个警告,即在设置缓冲句柄的值之前正在使用它。您不应该忽略这样的警告,因为您在sizing函数中的用法是不正确的。然而,这并不是问题所在。
我不认为你的两个测试用例有什么区别。你似乎不正确地解释了结果。
查看netlib文档,我们看到info
值为5平均U(5,5)
为零,这对于将来的使用将是有问题的。这并不意味着dgetrf
分解在打印出来时是成功的或不成功的,而是意味着有关输入数据的一些内容。事实上,正如文档中明确指出的那样,分解已经完成。
同样,我们只通过查看缓冲器函数的返回值就无法获得有关该条件的任何信息。为了发现与其值所报道的类似的信息。
通过这些更改,您的代码将报告相同的内容(信息值为5):
$ cat t1556.cu
#include <time.h>
#include <stdio.h>
#include <string.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <cusolverDn.h>
int main(int argc, char** argv){
const int matrixSize = 5;
int i, j;
double arrA[matrixSize][matrixSize] = {
{2.0, 4.0, 1.0, -3.0, 0.0},
{-1.0, -2.0, 2.0, 4.0, 0.0},
{4.0, 2.0, -3.0, 5.0, 0.0},
{5.0, -4.0, -3.0, 1.0, 0.0},
{0.0, 0.0, 0.0, 0.0, 0.0}
};
double *arrADev, *workArray;
double **matrixArray;
int *pivotArray;
int *infoArray;
double flat[matrixSize*matrixSize] = {0};
cublasHandle_t cublasHandle;
cublasStatus_t cublasStatus;
cudaError_t error;
cudaError cudaStatus;
cusolverStatus_t cusolverStatus;
cusolverDnHandle_t cusolverHandle;
double *matrices[2];
error = cudaMalloc(&arrADev, sizeof(double) * matrixSize*matrixSize);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
error = cudaMalloc(&matrixArray, sizeof(double*) * 2);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
error = cudaMalloc(&pivotArray, sizeof(int) * matrixSize*matrixSize);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
error = cudaMalloc(&infoArray, sizeof(int) * matrixSize*matrixSize);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
cublasStatus = cublasCreate(&cublasHandle);
if (cublasStatus != CUBLAS_STATUS_SUCCESS) fprintf(stderr,"error %i\n",cublasStatus);
//maps matrix to flat vector
for(i=0; i<matrixSize; i++){
for(j=0; j<matrixSize; j++){
flat[i+j*matrixSize] = arrA[i][j];
}
}
//copy matrix A to device
cublasStatus = cublasSetMatrix(matrixSize, matrixSize, sizeof(double), flat, matrixSize, arrADev, matrixSize);
if (cublasStatus != CUBLAS_STATUS_SUCCESS) fprintf(stderr,"error %i\n",cublasStatus);
//save matrix address
matrices[0] = arrADev;
//copy matrices references to device
error = cudaMemcpy(matrixArray, matrices, sizeof(double*)*1, cudaMemcpyHostToDevice);
if (error != cudaSuccess) fprintf(stderr,"\nError: %s\n",cudaGetErrorString(error));
int Lwork;
// calculate buffer size for cuSOLVER LU factorization
cusolverStatus = cusolverDnCreate(&cusolverHandle);
cusolverStatus = cusolverDnDgetrf_bufferSize(cusolverHandle, matrixSize, matrixSize, arrADev, matrixSize, &Lwork);
cudaStatus = cudaMalloc((void**)&workArray, Lwork*sizeof(double));
// cuBLAS LU factorization
cublasStatus = cublasDgetrfBatched(cublasHandle, matrixSize, matrixArray, matrixSize, pivotArray, infoArray, 1);
if (cublasStatus == CUBLAS_STATUS_SUCCESS)
printf("cuBLAS DGETRF SUCCESSFUL! \n");
else
printf("cuBLAS DGETRF UNSUCCESSFUL! \n");
// cuSOLVER LU factorization
cusolverStatus = cusolverDnDgetrf(cusolverHandle, matrixSize, matrixSize, arrADev, matrixSize, workArray, pivotArray, infoArray);
if (cusolverStatus == CUSOLVER_STATUS_SUCCESS)
printf("cuSOLVER DGETRF SUCCESSFUL! \n");
else
printf("cuSOLVER DGETRF UNSUCCESSFUL! \n");
int *hinfoArray = (int *)malloc(matrixSize*matrixSize*sizeof(int));
cudaMemcpy(hinfoArray, infoArray, matrixSize*matrixSize*sizeof(int), cudaMemcpyDeviceToHost);
for (int i = 0; i < matrixSize*matrixSize; i++) printf("%d,", hinfoArray[i]);
printf("\n");
return 0;
}
$ nvcc -o t1556 t1556.cu -lcublas -lcusolver
t1556.cu(30): warning: variable "cudaStatus" was set but never used
$ ./t1556
cuBLAS DGETRF SUCCESSFUL!
cuSOLVER DGETRF SUCCESSFUL!
5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
$ cat t1557.cpp
#include <iostream>
#include <vector>
#include <lapacke/lapacke.h>
using namespace std;
// extern "C" void dgetrf_(int* dim1, int* dim2, double* a, int* lda, int* ipiv, int* info);
// extern "C" void dgetrs_(char *TRANS, int *N, int *NRHS, double *A, int *LDA, int *IPIV, double *B, int *LDB, int *INFO );
int main()
{
char trans = 'N';
int dim = 5;
int LDA = dim;
int info;
vector<double> a,b;
a.push_back(2.0); a.push_back(4.0); a.push_back(1.0); a.push_back(-3.0); a.push_back(0.0);
a.push_back(-1.0); a.push_back(-2.0); a.push_back(2.0); a.push_back(4.0); a.push_back(0.0);
a.push_back(4.0); a.push_back(2.0); a.push_back(-3.0); a.push_back(5.0); a.push_back(0.0);
a.push_back(5.0); a.push_back(-4.0); a.push_back(-3.0); a.push_back(1.0); a.push_back(0.0);
a.push_back(0.0); a.push_back(0.0); a.push_back(0.0); a.push_back(0.0); a.push_back(0.0);
int ipiv[5];
LAPACK_dgetrf(&dim, &dim, &*a.begin(), &LDA, ipiv, &info);
printf("info = %d\n", info);
if (info == 0)
printf("dgetrf successful\n");
else
printf("dgetrf unsuccessful\n");
return 0;
}
$ g++ t1557.cpp -o t1557 -llapack
$ ./t1557
info = 5
dgetrf unsuccessful
$
我正在使用centOS安装的漏洞。
centOS 7,CUDA 10.1.243,Tesla V100.
https://stackoverflow.com/questions/58800010
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