How to properly handle errors in CUDA runtime API?

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1

I’ve been working with CUDA for a while now and I’m trying to figure out the best way to handle errors. I know there are functions like cudaGetLastError and cudaPeekAtLastError, but I’m not sure how to use them effectively. What’s the best practice for catching and reporting errors without making my code too cluttered? I want to make sure I’m not missing any important errors, but I also don’t want to add a ton of extra lines just for error checking.

Here’s a simple example of what I’m doing now:

__global__ void myKernel(int* data, int size) {
    int idx = blockIdx.x * blockDim.x + threadIdx.x;
    if (idx < size) {
        data[idx] *= 2;
    }
}

int main() {
    int* d_data;
    cudaMalloc(&d_data, sizeof(int) * 1000);
    myKernel<<<10, 100>>>(d_data, 1000);
    cudaFree(d_data);
    return 0;
}

How should I modify this to include proper error handling? Any advice would be really helpful!

2

Hey there! I’ve been working with CUDA for a while now, and error handling is definitely crucial. Here’s what I’ve found works well:

First, create a simple error-checking function:

void checkCudaErrors(cudaError_t result) {
    if (result != cudaSuccess) {
        fprintf(stderr, "CUDA error: %s\n", cudaGetErrorString(result));
        exit(-1);
    }
}

Then use it like this in your main function:

int main() {
    int* d_data;
    checkCudaErrors(cudaMalloc(&d_data, sizeof(int) * 1000));
    
    myKernel<<<10, 100>>>(d_data, 1000);
    checkCudaErrors(cudaGetLastError());
    checkCudaErrors(cudaDeviceSynchronize());
    
    checkCudaErrors(cudaFree(d_data));
    return 0;
}

This approach catches errors from both API calls and kernel launches without cluttering your code too much. It’s saved me countless hours of debugging!

3

yo, error handling in cuda can be tricky. i like to use a macro like this:

#define CUDA_CHECK(call) do {
cudaError_t err = call;
if (err != cudaSuccess) {
printf(“CUDA error at %s:%d: %s\n”, FILE, LINE,
cudaGetErrorString(err));
exit(EXIT_FAILURE);
}
} while(0)

then just wrap ur cuda calls like CUDA_CHECK(cudaMalloc(&d_data, size))

keeps things clean n catches errors quick

4

Error handling in CUDA is indeed crucial for robust applications. I’ve found that using a custom error-checking function can significantly streamline the process. Here’s an approach I’ve used successfully:

void checkCuda(cudaError_t result, char const *const func, const char *const file, int const line) {
    if (result != cudaSuccess) {
        fprintf(stderr, "CUDA error at %s:%d code=%d(%s) \"%s\"\n",
                file, line, static_cast<unsigned int>(result), cudaGetErrorString(result), func);
        cudaDeviceReset();
        exit(EXIT_FAILURE);
    }
}

#define checkCudaErrors(val) checkCuda((val), #val, __FILE__, __LINE__)

Then, you can use it like this:

int main() {
    int* d_data;
    checkCudaErrors(cudaMalloc(&d_data, sizeof(int) * 1000));
    myKernel<<<10, 100>>>(d_data, 1000);
    checkCudaErrors(cudaGetLastError());
    checkCudaErrors(cudaDeviceSynchronize());
    checkCudaErrors(cudaFree(d_data));
    return 0;
}

This approach provides detailed error information without cluttering your code. It’s been a game-changer for my CUDA projects.