cuSolver库较cuBLAS库更为高级，其能处理矩阵求逆，矩阵对角化，矩阵分解，特征值计算等问题。cuSolver库的实现是基于cuBLAS库和cuSPARSE库这两个基本库。cuSolver库的功能类似于Fortran中的LAPACK库：是Linear Algebra PACKage的简称。
以下以一个厄米矩阵的本征值（特征值）问题，代码示例cusolver.cu：
#include "error.cuh"
#include <stdio.h>
#include <stdlib.h>
#include <cusolverDn.h> //必须要用的头文件
int main(void)
{
int N = 2;
int N2 = N * N;
cuDoubleComplex *A_cpu = (cuDoubleComplex *) //定义一个cuDoubleComplex类型的双精度复数的主机数组A_cpu
malloc(sizeof(cuDoubleComplex) * N2); //分配一个大小为 N*N 的一维主机线性内存
for (int n = 0; n < N2; ++n)
{
A_cpu[0].x = 0;
A_cpu[1].x = 0;
A_cpu[2].x = 0;
A_cpu[3].x = 0;
A_cpu[0].y = 0;
A_cpu[1].y = 1; //复数元素0+i
A_cpu[2].y = -1; //复数元素0-i
A_cpu[3].y = 0;
}
cuDoubleComplex *A;
CHECK(cudaMalloc((void**)&A, sizeof(cuDoubleComplex) * N2)); //分配GPU显存
CHECK(cudaMemcpy(A, A_cpu, sizeof(cuDoubleComplex) * N2, //从主机A_cpu数组传到GPU数组A
cudaMemcpyHostToDevice));
double *W_cpu = (double*) malloc(sizeof(double) * N); //定义保存矩阵本征值的主机数组W_cpu
double *W;
CHECK(cudaMalloc((void**)&W, sizeof(double) * N)); //定义保存矩阵本征值的GPU数组W
cusolverDnHandle_t handle = NULL; //定义cusolverDnHandle类型的句柄
cusolverDnCreate(&handle); //初始化
cusolverEigMode_t jobz = CUSOLVER_EIG_MODE_NOVECTOR; //仅计算本征值不计算本征矢
cublasFillMode_t uplo = CUBLAS_FILL_MODE_LOWER; //用下三角矩阵填充
int lwork = 0;
cusolverDnZheevd_bufferSize(handle, jobz, uplo, //计算缓冲空间的大小
N, A, N, W, &lwork);
cuDoubleComplex* work;
CHECK(cudaMalloc((void**)&work,
sizeof(cuDoubleComplex) * lwork));
int* info;
CHECK(cudaMalloc((void**)&info, sizeof(int)));
cusolverDnZheevd(handle, jobz, uplo, N, A, N, W, //计算矩阵A的本征值W
work, lwork, info);
cudaMemcpy(W_cpu, W, sizeof(double) * N, //存到主机W_cpu中
cudaMemcpyDeviceToHost);
printf("Eigenvalues are:\n"); //打印结果
for (int n = 0; n < N; ++n)
{
printf("%g\n", W_cpu[n]);
}
cusolverDnDestroy(handle); //销毁句柄
free(A_cpu); //释放主机内存
free(W_cpu);
CHECK(cudaFree(A)); //释放GPU显存
CHECK(cudaFree(W));
CHECK(cudaFree(work));
CHECK(cudaFree(info));
return 0;
}头文件error.cuh为错误检查宏CHECK函数：文章来源：https://www.toymoban.com/news/detail-754459.html
#pragma once
#include <stdio.h>
#define CHECK(call) \
{ \
const cudaError_t error_code = call; \
if (error_code != cudaSuccess) \
{ \
printf("CUDA Error:\n"); \
printf(" File: %s\n", __FILE__); \
printf(" Line: %d\n", __LINE__); \
printf(" Error code: %d\n", error_code); \
printf(" Error text: %s\n", \
cudaGetErrorString(error_code)); \
exit(1); \
} \
}编译运行：文章来源地址https://www.toymoban.com/news/detail-754459.html
$ nvcc cusolver.cu -o cusolver
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