C++如何调用cusparse库进行矩阵乘法

在C++中调用CUSPARSE库进行矩阵乘法的步骤如下：

1. 包含CUSPARSE头文件

#include <cuda_runtime.h>
#include <cusparse.h>

2. 创建CUSPARSE句柄

cusparseHandle_t handle;
cusparseCreate(&handle);

3. 定义矩阵A和矩阵B

const int ROWS = 3;
const int COLS = 3;
const int NNZ = 9;
float h_A[NNZ] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
float h_B[NNZ] = {9.0, 8.0, 7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0};

4. 将矩阵A和矩阵B复制到设备端

float *d_A, *d_B;
cudaMalloc((void**)&d_A, NNZ*sizeof(float));
cudaMalloc((void**)&d_B, NNZ*sizeof(float));
cudaMemcpy(d_A, h_A, NNZ*sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(d_B, h_B, NNZ*sizeof(float), cudaMemcpyHostToDevice);

5. 定义矩阵A、B、C在CUSPARSE中的描述符

cusparseMatDescr_t descrA, descrB, descrC;
cusparseCreateMatDescr(&descrA);
cusparseCreateMatDescr(&descrB);
cusparseCreateMatDescr(&descrC);
cusparseSetMatType(descrA, CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatType(descrB, CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatType(descrC, CUSPARSE_MATRIX_TYPE_GENERAL);
cusparseSetMatIndexBase(descrA, CUSPARSE_INDEX_BASE_ZERO);
cusparseSetMatIndexBase(descrB, CUSPARSE_INDEX_BASE_ZERO);
cusparseSetMatIndexBase(descrC, CUSPARSE_INDEX_BASE_ZERO);

6. 定义矩阵A、B、C在CUSPARSE中的行指针、列下标和数值

int *d_A_row_ptr, *d_A_col_idx, *d_B_row_ptr, *d_B_col_idx, *d_C_row_ptr, *d_C_col_idx;
float *d_C_val;
cudaMalloc((void**)&d_A_row_ptr, (ROWS+1)*sizeof(int));
cudaMalloc((void**)&d_A_col_idx, NNZ*sizeof(int));
cudaMalloc((void**)&d_B_row_ptr, (ROWS+1)*sizeof(int));
cudaMalloc((void**)&d_B_col_idx, NNZ*sizeof(int));
cudaMalloc((void**)&d_C_row_ptr, (ROWS+1)*sizeof(int));
cudaMalloc((void**)&d_C_col_idx, NNZ_C*sizeof(int));
cudaMalloc((void**)&d_C_val, NNZ_C*sizeof(float));
cudaMemcpy(d_A_row_ptr, h_A_row_ptr, (ROWS+1)*sizeof(int), cudaMemcpyHostToDevice);
cudaMemcpy(d_A_col_idx, h_A_col_idx, NNZ*sizeof(int), cudaMemcpyHostToDevice);
cudaMemcpy(d_B_row_ptr, h_B_row_ptr, (ROWS+1)*sizeof(int), cudaMemcpyHostToDevice);
cudaMemcpy(d_B_col_idx, h_B_col_idx, NNZ*sizeof(int), cudaMemcpyHostToDevice);

7. 计算矩阵C

cusparseScsrmult(handle, CUSPARSE_OPERATION_NON_TRANSPOSE, CUSPARSE_OPERATION_NON_TRANSPOSE, ROWS, ROWS, COLS, &NNZ, 
                 &alpha, descrA, d_A_val, d_A_row_ptr, d_A_col_idx, descrB, d_B_val, d_B_row_ptr, d_B_col_idx, 
                 &beta, descrC, d_C_val, d_C_row_ptr, d_C_col_idx);

8. 将矩阵C从设备端复制到主机端

float h_C[NNZ_C] = {0};
cudaMemcpy(h_C, d_C_val, NNZ_C*sizeof(float), cudaMemcpyDeviceToHost);

9. 释放内存

cusparseDestroyMatDescr(descrA);
cusparseDestroyMatDescr(descrB);
cusparseDestroyMatDescr(descrC);
cusparseDestroy(handle);
cudaFree(d_A);
cudaFree(d_B);
cudaFree(d_A_row_ptr);
cudaFree(d_A_col_idx);
cudaFree(d_B_row_ptr);
cudaFree(d_B_col_idx);
cudaFree(d_C_row_ptr);
cudaFree(d_C_col_idx);
cudaFree(d_C_val);

这样，就完成了利用CUSPARSE库进行矩阵乘法的过程。需要注意的是，CUSPARSE库中支持多种矩阵格式，如CSR、CSC、COO等，需要根据实际问题选择合适的矩阵格式。同时，CUSPARSE库还支持多种矩阵操作，如转置、求逆等，具体使用方法可以参考CUSPARSE库的文档。