CUBLAS: Incorrect inversion for matrix with zero pivot

Question

Since CUDA 5.5, the CUBLAS library contains routines for batched matrix factorization and inversion (cublasgetrfBatched and cublasgetriBatched respectively

Answer 1

There seems to be a bug in the current CUBLAS library implementation of cublasgetrfBatched for matrices of dimension (n) such that 3<=n<=16, when there is a "zero pivot" as you say.

A possible workaround is to "identity-extend" your A matrix to be inverted, when n<17, to a size of 17x17 (using matlab nomenclature):

 LU = getrf( [A 0 ; 0 I]);

continuing, you can then use cublasgetriBatched in an "ordinary" fashion:

 invA = getri( LU(1:3,1:3) )

(You can also leave everything at n=17, call getri that way, and then extract the result as the first 3x3 rows and columns of invA.)

Here is a fully worked example, borrowing from the code you supplied, showing the inversion of your supplied 3x3 zero_pivot matrix, using the zero_pivot_war matrix as an "identity-extended" workaround:

$ cat t340.cu
#include 
#include 
#include 
#include 

#define cudacall(call)                                                                                                          \
    do                                                                                                                          \
    {                                                                                                                           \
        cudaError_t err = (call);                                                                                               \
        if(cudaSuccess != err)                                                                                                  \
        {                                                                                                                       \
            fprintf(stderr,"CUDA Error:\nFile = %s\nLine = %d\nReason = %s\n", __FILE__, __LINE__, cudaGetErrorString(err));    \
            cudaDeviceReset();                                                                                                  \
            exit(EXIT_FAILURE);                                                                                                 \
        }                                                                                                                       \
    }                                                                                                                           \
    while (0)

#define cublascall(call)                                                                                        \
    do                                                                                                          \
    {                                                                                                           \
        cublasStatus_t status = (call);                                                                         \
        if(CUBLAS_STATUS_SUCCESS != status)                                                                     \
        {                                                                                                       \
            fprintf(stderr,"CUBLAS Error:\nFile = %s\nLine = %d\nCode = %d\n", __FILE__, __LINE__, status);     \
            cudaDeviceReset();                                                                                  \
            exit(EXIT_FAILURE);                                                                                 \
        }                                                                                                       \
                                                                                                                \
    }                                                                                                           \
    while(0)


void invert_device(float* src_d, float* dst_d, int n)
{
    cublasHandle_t handle;
    cublascall(cublasCreate_v2(&handle));

    int batchSize = 1;

    int *P, *INFO;

    cudacall(cudaMalloc(&P,17 * batchSize * sizeof(int)));
    cudacall(cudaMalloc(&INFO,batchSize * sizeof(int)));

    int lda = 17;

    float *A[] = { src_d };
    float** A_d;
    cudacall(cudaMalloc(&A_d,sizeof(A)));
    cudacall(cudaMemcpy(A_d,A,sizeof(A),cudaMemcpyHostToDevice));

    cublascall(cublasSgetrfBatched(handle,17,A_d,lda,P,INFO,batchSize));

    int INFOh = 0;
    cudacall(cudaMemcpy(&INFOh,INFO,sizeof(int),cudaMemcpyDeviceToHost));

    if(INFOh == 17)
    {
        fprintf(stderr, "Factorization Failed: Matrix is singular\n");
        cudaDeviceReset();
        exit(EXIT_FAILURE);
    }

    float* C[] = { dst_d };
    float** C_d;
    cudacall(cudaMalloc(&C_d,sizeof(C)));
    cudacall(cudaMemcpy(C_d,C,sizeof(C),cudaMemcpyHostToDevice));

    cublascall(cublasSgetriBatched(handle,n,A_d,lda,P,C_d,n,INFO,batchSize));

    cudacall(cudaMemcpy(&INFOh,INFO,sizeof(int),cudaMemcpyDeviceToHost));

    if(INFOh != 0)
    {
        fprintf(stderr, "Inversion Failed: Matrix is singular\n");
        cudaDeviceReset();
        exit(EXIT_FAILURE);
    }

    cudaFree(P), cudaFree(INFO), cublasDestroy_v2(handle);
}

void invert(float* src, float* dst, int n)
{
    float* src_d, *dst_d;

    cudacall(cudaMalloc(&src_d,17 * 17 * sizeof(float)));
    cudacall(cudaMemcpy(src_d,src,17 * 17 * sizeof(float),cudaMemcpyHostToDevice));
    cudacall(cudaMalloc(&dst_d,n * n * sizeof(float)));

    invert_device(src_d,dst_d,n);

    cudacall(cudaMemcpy(dst,dst_d,n * n * sizeof(float),cudaMemcpyDeviceToHost));

    cudaFree(src_d), cudaFree(dst_d);
}

void test_invert()
{
    const int n = 3;

    //Random matrix with full pivots
/*    float full_pivots[n*n] = { 0.5, 3, 4,
                                1, 3, 10,
                                4 , 9, 16 };

    //Almost same as above matrix with first pivot zero
    float zero_pivot[n*n] = { 0, 3, 4,
                              1, 3, 10,
                              4 , 9, 16 };

    float zero_pivot_col_major[n*n] = { 0, 1, 4,
                                        3, 3, 9,
                                        4 , 10, 16 };
*/
    float zero_pivot_war[17*17] = {
                                        0,3,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
                                        1,3,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
                                        4,9,16,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
                                        0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,
                                        0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,
                                        0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,
                                        0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,
                                        0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,
                                        0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,
                                        0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,
                                        0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,
                                        0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,
                                        0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,
                                        0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,
                                        0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,
                                        0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,
                                        0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1 };
/*
    float another_zero_pivot[n*n] = { 0, 3, 4,
                                      1, 5, 6,
                                      9, 8, 2 };

    float another_full_pivot[n * n] = { 22, 3, 4,
                                        1, 5, 6,
                                        9, 8, 2 };

    float singular[n*n] = {1,2,3,
                           4,5,6,
                           7,8,9};
*/
    float result[n*n];

    //Select matrix by setting "a"
    float* a = zero_pivot_war;

    fprintf(stdout, "Input:\n\n");
    for(int i=0; i

The above result appears to me to be correct based on a simple test elsewhere.

I don't have any further technical details about the nature of the possible bug in CUBLAS. From what I can tell, it is present in both CUDA 5.5 and CUDA 6.0 RC. Detailed bug discussions for NVIDIA-supplied assets (e.g. CUBLAS library) should be taken up on the NVIDIA developer forums or directly at the bug filing portal on developer.nvidia.com (you must be a registered developer to file a bug).