internal error when trying to perform matrix transpose using cusparseCsr2cscEx2() function of cuSPARSE

Question

I am need to perform transpose of a matrix(CSR) using cuSPARSE, but get “internal error”. I write my code referring to How to transpose a sparse matrix in cuSparse? and https://docs.nvidia.com/cuda/cusparse/index.html#csr2cscEx2. To make it more clearly, I am trying to perform transpose by convert the matrix from format csr to format csc.

I am running on Nvidia GeForce GTX 1080, with driver cuda_11.1.0. I am using Windows 10.

The following is my codes. You can download the folder from https://github.com/NVIDIA/CUDALibrarySamples/tree/master/cuSPARSE/sparse2dense, and replace the sparse2dense_example.c with my codes. Then configure and make using CMake, in this way maybe you can reproduce my problems.

#include <cuda_runtime_api.h> // cudaMalloc, cudaMemcpy, etc.
#include <cusparse.h>         // cusparseSparseToDense
#include <stdio.h>            // printf
#include <stdlib.h>           // EXIT_FAILURE

#define CHECK_CUDA(func)                                                       \
{                                                                              \
    cudaError_t status = (func);                                               \
    if (status != cudaSuccess) {                                               \
        printf("CUDA API failed at line %d with error: %s (%d)\n",             \
               __LINE__, cudaGetErrorString(status), status);                  \
        return EXIT_FAILURE;                                                   \
    }                                                                          \
}

#define CHECK_CUSPARSE(func)                                                   \
{                                                                              \
    cusparseStatus_t status = (func);                                          \
    if (status != CUSPARSE_STATUS_SUCCESS) {                                   \
        printf("CUSPARSE API failed at line %d with error: %s (%d)\n",         \
               __LINE__, cusparseGetErrorString(status), status);              \
        return EXIT_FAILURE;                                                   \
    }                                                                          \
}

int main(void) {
    // CUSPARSE APIs
    cusparseHandle_t     handle = NULL;
    cusparseStatus_t status = (cusparseCreate(&handle));
    if (status != CUSPARSE_STATUS_SUCCESS) {
        printf("CUSPARSE API failed at line %d with error: %s (%d)\n", __LINE__, cusparseGetErrorString(status), status);
    }
    
    // Initialize matrix A
    // this matrix is the same as https://github.com/NVIDIA/CUDALibrarySamples/blob/master/cuSPARSE/sparse2dense/sparse2dense_example.c
    int   num_rows = 5;
    int   num_cols = 4;
    int   nnz = 11;
    int   h_csr_offsets[] = { 0, 3, 4, 7, 9, 11 };
    int   h_csr_columns[] = { 0, 2, 3, 1, 0, 2, 3, 1, 3, 1, 2 };
    float h_csr_values[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f,
                               7.0f, 8.0f, 9.0f, 10.0f, 11.0f };
    // Device memory management
    int* d_csr_offsets, * d_csr_columns;
    float* d_csr_values;
    CHECK_CUDA(cudaMalloc((void**)&d_csr_offsets, (num_rows + 1) * sizeof(int)))
    CHECK_CUDA(cudaMalloc((void**)&d_csr_columns, nnz * sizeof(int)))
    CHECK_CUDA(cudaMalloc((void**)&d_csr_values, nnz * sizeof(float)))

    CHECK_CUDA(cudaMemcpy(d_csr_offsets, h_csr_offsets, (num_rows + 1) * sizeof(int), cudaMemcpyHostToDevice))
    CHECK_CUDA(cudaMemcpy(d_csr_columns, h_csr_columns, nnz * sizeof(int), cudaMemcpyHostToDevice))
    CHECK_CUDA(cudaMemcpy(d_csr_values, h_csr_values, nnz * sizeof(float), cudaMemcpyHostToDevice))

    // Memory allocation of transpose A
    int* d_csr_offsets_AT, * d_csr_columns_AT;
    float* d_csr_values_AT;
    //first allocate memory to ATT
    CHECK_CUDA(cudaMalloc((void**)&d_csr_offsets_AT, (num_cols + 1) * sizeof(int)))
    CHECK_CUDA(cudaMalloc((void**)&d_csr_columns_AT, nnz * sizeof(int)))
    CHECK_CUDA(cudaMalloc((void**)&d_csr_values_AT, nnz * sizeof(float)))

    size_t buffer_temp_size;
    cusparseCsr2cscEx2_bufferSize(
        handle, num_rows, num_cols, nnz, h_csr_values, h_csr_offsets, h_csr_columns,
        d_csr_values_AT, d_csr_offsets_AT, d_csr_columns_AT, CUDA_R_32F, CUSPARSE_ACTION_NUMERIC,
        CUSPARSE_INDEX_BASE_ZERO, CUSPARSE_CSR2CSC_ALG1, &buffer_temp_size);
    void* buffer_temp = NULL;
    printf("buffer_temp_size is %zd\n", buffer_temp_size);
    CHECK_CUDA(cudaMalloc(&buffer_temp, buffer_temp_size))
    CHECK_CUSPARSE(cusparseCsr2cscEx2(handle, num_rows, num_cols, nnz, h_csr_values, h_csr_offsets, h_csr_columns,
        d_csr_values_AT, d_csr_offsets_AT, d_csr_columns_AT, CUDA_R_32F, CUSPARSE_ACTION_NUMERIC,
        CUSPARSE_INDEX_BASE_ZERO, CUSPARSE_CSR2CSC_ALG1, buffer_temp))
}

Robert Crovella · Accepted Answer · 2020-12-09 15:32:18Z

1

The error is due to the fact that you are passing pointers to host data, to a routine that intends to work on device data:

cusparseCsr2cscEx2_bufferSize(
    handle, num_rows, num_cols, nnz, h_csr_values, h_csr_offsets, h_csr_columns,
                                     ^             ^              ^

and

CHECK_CUSPARSE(cusparseCsr2cscEx2(handle, num_rows, num_cols, nnz, h_csr_values, h_csr_offsets, h_csr_columns,
                                                                   ^             ^              ^

When I change those instances to your allocated device data:

d_csr_values, d_csr_offsets, d_csr_columns

the "internal error" that you are asking about goes away, according to my testing.

answered Dec 9, 2020 at 15:32

Robert Crovella

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