CODEWITHSUNDEEP
cuda
user2412789
user2412789

Reputation: 113

Dynamic parallelism cudaDeviceSynchronize() crashes

I have a kernel which calls another empty kernel. However when the calling kernel calls cudaDeviceSynchronize(), the kernel crashes and the execution goes straight to the host. Memory checker does not report of any memory access issues. Does anyone know what could be the reason for such uncivilized behavior?

The crash seems to happen only if I run the code from the debugger (Visual Studio -> Nsight -> Start CUDA Debugging). The crash does not happen every time I run the code - sometimes it crashes, and sometimes it finishes ok.

Here is the complete code to reproduce the problem:

#include <cuda_runtime.h>
#include <curand_kernel.h>
#include "device_launch_parameters.h"
#include <stdio.h>

#define CUDA_RUN(x_, err_) {cudaStatus = x_; if (cudaStatus != cudaSuccess) {fprintf(stderr, err_ "  %d - %s\n", cudaStatus, cudaGetErrorString(cudaStatus)); int k; scanf("%d", &k); goto Error;}}

struct computationalStorage {
    float rotMat;
};

__global__ void drawThetaFromDistribution() {}

__global__ void chainKernel() {
    computationalStorage* c = (computationalStorage*)malloc(sizeof(computationalStorage));
    if (!c) printf("malloc error\n");
    c->rotMat = 1.0f;

    int n = 1;
    while (n < 1000) {
        cudaError_t err;

        drawThetaFromDistribution<<<1, 1>>>();
        if ((err = cudaGetLastError()) != cudaSuccess)
            printf("drawThetaFromDistribution Sync kernel error: %s\n", cudaGetErrorString(err));
        printf("0");
        if ((err = cudaDeviceSynchronize()) != cudaSuccess)
          printf("drawThetaFromDistribution Async kernel error: %s\n", cudaGetErrorString(err));
        printf("1\n");
        ++n;
    }

    free(c);
}

int main() {
    cudaError_t cudaStatus;
    // Choose which GPU to run on, change this on a multi-GPU system.
    CUDA_RUN(cudaSetDevice(0), "cudaSetDevice failed!  Do you have a CUDA-capable GPU installed?");

    // Set to use on chip memory 16KB for shared, 48KB for L1
    CUDA_RUN(cudaDeviceSetCacheConfig ( cudaFuncCachePreferL1 ), "Can't set CUDA to use on chip memory for L1");
    // Set a large heap
    CUDA_RUN(cudaDeviceSetLimit(cudaLimitMallocHeapSize, 1024 * 10 * 192), "Can't set the Heap size");

    chainKernel<<<10, 192>>>();
    cudaStatus = cudaDeviceSynchronize();
    if (cudaStatus != cudaSuccess) {
        printf("Something was wrong! Error code: %d", cudaStatus);
    }

    CUDA_RUN(cudaDeviceReset(), "cudaDeviceReset failed!");

Error:
    int k;
    scanf("%d",&k);
    return 0;
}

If all goes well I expect to see:

00000000000000000000000....0000000000000001
1
1
1
1
....

This is what I get when everything works ok. When it crashes however:

000000000000....0000000000000Something was wrong! Error code: 30

As you can see the statement err = cudaDeviceSynchronize(); does not finish, and the execution goes straight to the host, where its cudaDeviceSynchronize(); fails with unknown error code (30 = cudaErrorUnknown).

System: CUDA 5.5, NVidia-Titan(Headless), Windows 7x64, Win32 application. UPDATE: additional Nvidia card driving the display, Nsight 3.2.0.13289.

Upvotes: 0

Views: 2647

Answers (1)

Robert Crovella
Robert Crovella

Reputation: 151879

That last fact may have been the critical one. You don't mention which version of nsight VSE you are using nor your exact machine config (e.g. are there other GPUs in the machine, if so, which is driving the display?), but at least up till recently it was not possible to debug a dynamic parallelism application in single-GPU mode with nsight VSE.

The current feature matrix also suggests that single-GPU CDP debugging is not yet supported.

Probably one possible workaround in your case would be to add another GPU to drive the display, and make the Titan card headless (i.e. don't attach any monitors and don't extend the windows desktop onto that GPU).

I ran your application with and without cuda-memcheck and it does not appear to me that there are any problems with it.

Upvotes: 1

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