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svd - cuda-memcheck error in cusolverDnCgesvdjBatched function using CUDA

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svd - cuda-memcheck error in cusolverDnCgesvdjBatched function using CUDA

I am using cusolverDnCgesvdjBatched function to calculate singular value decomposition (SVD) of multiple matrices, I use cuda-memcheck to check any memory issues, I am getting an error like this in the cusolverDnCgesvdjBatched function.

========= Invalid __global__ write of size 4
=========     at 0x000062f8 in void batched_svd_parallel_jacobi_32x16<float2, float>(int, int, int, int, float2*, __int64, int, float*, float2*, __int64, int, float2*, __int64, int, float, int, int*, float, int, int*, int, float)
=========     by thread (0,0,0) in block (4,0,0)
=========     Address 0x701019010 is out of bounds
=========     Saved host backtrace up to driver entry point at kernel launch time
=========     Host 
========= Program hit CUDA_ERROR_LAUNCH_FAILED (error 719) due to "unspecified launch failure" on CUDA API call to cuModuleUnload.
=========     Saved host backtrace up to driver entry point at error
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuProfilerStop + 0x904ce) [0x2ae05e]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuProfilerStop + 0x92e73) [0x2b0a03]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll [0x84cb7]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll [0x86e03]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuProfilerStop + 0x11473a) [0x3322ca]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuModuleUnload + 0x1d6) [0x1d5d36]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::module::unload + 0x115) [0x9535]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::contextState::unloadAllModules + 0x196) [0x9b36]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::contextStateManager::destroyAllContextStatesOnRuntimeUnload + 0x78) [0xa188]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::globalState::~globalState + 0x3d) [0x24dd]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::set<cudart::globalModule * __ptr64>::rehash + 0x106) [0x74c6]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (execute_onexit_table + 0x156) [0x142d6]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (execute_onexit_table + 0x7b) [0x141fb]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (execute_onexit_table + 0x34) [0x141b4]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (exit + 0x142) [0x20522]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (exit + 0xcb) [0x204ab]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (exit + 0x6e) [0x2044e]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (gpuErrchk + 0x4c) [0xf0dc]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (main + 0x3ef) [0xebaf]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (__scrt_common_main_seh + 0x10c) [0xf5c4]
=========     Host Frame:C:WINDOWSSystem32KERNEL32.dll (BaseThreadInitThunk + 0x14) [0x17034]
=========     Host Frame:C:WINDOWSSYSTEM32
tdll.dll (RtlUserThreadStart + 0x21) [0x52651]
=========
========= Program hit CUDA_ERROR_LAUNCH_FAILED (error 719) due to "unspecified launch failure" on CUDA API call to cuModuleUnload.
=========     Saved host backtrace up to driver entry point at error
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuProfilerStop + 0x904ce) [0x2ae05e]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuProfilerStop + 0x92e73) [0x2b0a03]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll [0x84cb7]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll [0x86e03]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuProfilerStop + 0x11473a) [0x3322ca]
=========     Host Frame:C:WINDOWSsystem32DriverStoreFileRepository
vami.inf_amd64_72390dc4652f28fa
vcuda64.dll (cuModuleUnload + 0x1d6) [0x1d5d36]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::module::unload + 0x115) [0x9535]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::contextState::unloadAllModules + 0x196) [0x9b36]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::contextStateManager::destroyAllContextStatesOnRuntimeUnload + 0x78) [0xa188]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::globalState::~globalState + 0x3d) [0x24dd]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (cudart::set<cudart::globalModule * __ptr64>::rehash + 0x106) [0x74c6]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (execute_onexit_table + 0x156) [0x142d6]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (execute_onexit_table + 0x7b) [0x141fb]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (execute_onexit_table + 0x34) [0x141b4]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (exit + 0x142) [0x20522]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (exit + 0xcb) [0x204ab]
=========     Host Frame:C:WINDOWSSystem32ucrtbase.dll (exit + 0x6e) [0x2044e]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (gpuErrchk + 0x4c) [0xf0dc]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (main + 0x3ef) [0xebaf]
=========     Host Frame:D:SVDx64ReleaseSVD.exe (__scrt_common_main_seh + 0x10c) [0xf5c4]
=========     Host Frame:C:WINDOWSSystem32KERNEL32.dll (BaseThreadInitThunk + 0x14) [0x17034]
=========     Host Frame:C:WINDOWSSYSTEM32
tdll.dll (RtlUserThreadStart + 0x21) [0x52651]
=========
========= ERROR SUMMARY: 8 errors

I am attaching the whole code I am using.

kernel.cu

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>

#include <cuda_runtime.h>
#include <cusolverDn.h>

#include "Utilities.cuh"
#include "TimingGPU.cuh"

#define FULLSVD
#define PRINTRESULTS

/********/
/* MAIN */
/********/
int main() {

    const int           M = 10;
    const int           N = 5;
    const int           lda = M;
    //const int         numMatrices = 3;
    const int           numMatrices = 256;

    TimingGPU timerGPU;

    // --- Setting the host matrix
    cuComplex *h_A = (cuComplex *)malloc(lda * N * numMatrices * sizeof(double));
    for (unsigned int k = 0; k < numMatrices; k++)
        for (unsigned int i = 0; i < M; i++)
        {
            for (unsigned int j = 0; j < N; j++)
            {
                h_A[k * M * N + j * M + i] = make_float2((1. / (k + 1)) * (i + j * j) * (i + j), (1. / (k + 1)) * (i + j * j) * (i + j));
                //printf("[%d, %d] %f
", i, j, h_A[j*M + i]);
                //printf("%f %f", h_A[j*M + i].x, h_A[j * M + i].y);
            }
            //printf("
");
        }

    // --- Setting the device matrix and moving the host matrix to the device
    cuComplex *d_A;         gpuErrchk(cudaMalloc(&d_A, M * N * numMatrices * sizeof(cuComplex)));
    gpuErrchk(cudaMemcpy(d_A, h_A, M * N * numMatrices * sizeof(cuComplex), cudaMemcpyHostToDevice));

    // --- host side SVD results space
    float *h_S = (float *)malloc(N * numMatrices * sizeof(float));
    cuComplex *h_U = NULL;
    cuComplex *h_V = NULL;
#ifdef FULLSVD
    h_U = (cuComplex *)malloc(M * M * numMatrices * sizeof(cuComplex));
    h_V = (cuComplex *)malloc(N * N * numMatrices * sizeof(cuComplex));
#endif

    // --- device side SVD workspace and matrices
    int work_size = 0;

    int *devInfo;        gpuErrchk(cudaMalloc(&devInfo, sizeof(int)));
    float *d_S;         gpuErrchk(cudaMalloc(&d_S, N * numMatrices * sizeof(float)));
    cuComplex *d_U = NULL;
    cuComplex *d_V = NULL;
#ifdef FULLSVD
    gpuErrchk(cudaMalloc(&d_U, M * M * numMatrices * sizeof(cuComplex)));
    gpuErrchk(cudaMalloc(&d_V, N * N * numMatrices * sizeof(cuComplex)));
#endif

    cuComplex *d_work = NULL; /* devie workspace for gesvdj */
    int devInfo_h = 0; /* host copy of error devInfo_h */

    // --- Parameters configuration of Jacobi-based SVD
    const double            tol = 1.e-7;
    const int               maxSweeps = 15;
    cusolverEigMode_t jobz;                                   // --- CUSOLVER_EIG_MODE_VECTOR - Compute eigenvectors; CUSOLVER_EIG_MODE_NOVECTOR - Compute singular values only
#ifdef FULLSVD
    jobz = CUSOLVER_EIG_MODE_VECTOR;
#else
    jobz = CUSOLVER_EIG_MODE_NOVECTOR;
#endif

    const int               econ = 0;                            // --- econ = 1 for economy size 

    // --- Numerical result parameters of gesvdj 
    double                  residual = 0;
    int                     executedSweeps = 0;

    // --- CUDA solver initialization
    cusolverDnHandle_t solver_handle = NULL;
    cusolveSafeCall(cusolverDnCreate(&solver_handle));

    // --- Configuration of gesvdj
    gesvdjInfo_t gesvdj_params = NULL;
    cusolveSafeCall(cusolverDnCreateGesvdjInfo(&gesvdj_params));

    // --- Set the computation tolerance, since the default tolerance is machine precision
    cusolveSafeCall(cusolverDnXgesvdjSetTolerance(gesvdj_params, tol));

    // --- Set the maximum number of sweeps, since the default value of max. sweeps is 100
    cusolveSafeCall(cusolverDnXgesvdjSetMaxSweeps(gesvdj_params, maxSweeps));

    // --- Query the SVD workspace 
    cusolveSafeCall(cusolverDnCgesvdjBatched_bufferSize(
        solver_handle,
        jobz,                                       // --- Compute the singular vectors or not
        M,                                          // --- Number of rows of A, 0 <= M
        N,                                          // --- Number of columns of A, 0 <= N 
        d_A,                                        // --- M x N
        lda,                                        // --- Leading dimension of A
        d_S,                                        // --- Square matrix of size min(M, N) x min(M, N)
        d_U,                                        // --- M x M if econ = 0, M x min(M, N) if econ = 1
        lda,                                        // --- Leading dimension of U, ldu >= max(1, M)
        d_V,                                        // --- N x N if econ = 0, N x min(M,N) if econ = 1
        lda,                                        // --- Leading dimension of V, ldv >= max(1, N)
        &work_size,
        gesvdj_params,
        numMatrices));

    gpuErrchk(cudaMalloc(&d_work, sizeof(cuComplex) * work_size));

    // --- Compute SVD
    timerGPU.StartCounter();
    cusolveSafeCall(cusolverDnCgesvdjBatched(
        solver_handle,
        jobz,                                       // --- Compute the singular vectors or not
        M,                                          // --- Number of rows of A, 0 <= M
        N,                                          // --- Number of columns of A, 0 <= N 
        d_A,                                        // --- M x N
        lda,                                        // --- Leading dimension of A
        d_S,                                        // --- Square matrix of size min(M, N) x min(M, N)
        d_U,                                        // --- M x M if econ = 0, M x min(M, N) if econ = 1
        lda,                                        // --- Leading dimension of U, ldu >= max(1, M)
        d_V,                                        // --- N

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1 Reply

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Referring to the documentation, for the info parameter:

info device output an integer array of dimension batchSize

So this is expected to be an array of integers of size equal to the number of matrices in the batch. This makes sense because we expect one of these info reports for each matrix. But your allocation does not do that:

int *devInfo;        gpuErrchk(cudaMalloc(&devInfo, sizeof(int)));

When I fix that:

int *devInfo;        gpuErrchk(cudaMalloc(&devInfo, sizeof(int) * numMatrices));

the error goes away for me. This also has implications for your host-side allocation and also the copying of this data from device to host, later in the code.


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