Weird CUDA error in a very simple test [duplicate] - cuda

Question

I am new to CUDA. When I multiply the 1024x1024 matrix, and launch a kernel with:
multiplyKernel << <dim3(32,32, 1), dim3(32, 32, 1) >> >(dev_c, dev_a, dev_b, size);
But when I multiply a 2048 x 2048 matrix, with
dim3(64,64,1)
I get this error:
cudaDeviceSynchronize returned error code 4 after launching addKernel!
unspecified launch failure
From tinkering with the code, I think that the error is in this statement
result += a[row * size + ind] * b[col + size * ind];
in the part
b[col+size*ind]
If I take that out, I don't get a kernel launch error (just the wrong answer, obviously). I cannot figure out what's wrong. Any suggestions would be most appreciated.
I am using Visual Studio 2013. I am using the debugger, but this does not help me find the error.
This seems to be a similar problem:
cudaDeviceSynchronize returned error code 4 after launching
many thanks, here is the code:
cudaError_t multiplyWithCuda(int *c, const int *a, const int *b, unsigned int size);
__global__ void multiplyKernel(int *c, const int *a, const int *b, unsigned int size)
{
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
if (row > size || col > size) return;
// target field in 1-D
int z = row * size + col;
int result = 0;
for (int ind = 0; ind < size ; ++ind) {
result += a[row * size + ind] * b[col + size * ind];
}
c[z] = result;
}
int main(){
const int sizeMatrix = 2048;
int* a = new int[sizeMatrix * sizeMatrix];
int* b = new int[sizeMatrix * sizeMatrix];
int* c = new int[sizeMatrix * sizeMatrix];
for (int i = 0; i < sizeMatrix * sizeMatrix; i++) {
a[i] = rand() % 2;
b[i] = rand() % 2;
}
cudaError_t cudaStatus = multiplyWithCuda(c, a, b, sizeMatrix);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "addWithCuda failed!");
return 1;
}
cudaStatus = cudaDeviceReset();
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaDeviceReset failed!");
return 1;
}
return 0;
}
cudaError_t multiplyWithCuda(int *c, const int *a, const int *b, unsigned int size)
{
int *dev_a ;
int *dev_b;
int *dev_c;
cudaError_t cudaStatus;
// Choose which GPU to run on, change this on a multi-GPU system.
cudaStatus = cudaSetDevice(0);
fprintf(stdout, "device set");
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaSetDevice failed! Do you have a CUDA-capable GPU installed?");
goto Error;
}
// Allocate GPU buffers for three vectors (two input, one output) .
cudaStatus = cudaMalloc((void**)&dev_c, size * size * sizeof(int));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
goto Error;
}
fprintf(stdout, "buffer for c allocated \n");
cudaStatus = cudaMalloc((void**)&dev_a, size * size * sizeof(int));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
goto Error;
}
fprintf(stdout, "buffer for a allocated \n");
cudaStatus = cudaMalloc((void**)&dev_b, size * size * sizeof(int));
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMalloc failed!");
goto Error;
}
fprintf(stdout, "buffer for b allocated \n");
// Copy input vectors from host memory to GPU buffers.
cudaStatus = cudaMemcpy(dev_a, a, size * size * sizeof(int), cudaMemcpyHostToDevice);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
goto Error;
}
fprintf(stdout, "cudaMemcpy a done \n");
cudaStatus = cudaMemcpy(dev_b, b, size * size * sizeof(int), cudaMemcpyHostToDevice);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
goto Error;
}
fprintf(stdout, "cudaMemcpy b done\n");
fprintf(stdout, "about to launch kernel \n");
// Launch a kernel on the GPU with one thread for each element.
multiplyKernel << <dim3(64,64, 1), dim3(32, 32, 1) >> >(dev_c, dev_a, dev_b, size);
fprintf(stdout, "kernel launched\n");
// Check for any errors launching the kernel
cudaStatus = cudaGetLastError();
if (cudaStatus != cudaSuccess) {
; fprintf(stderr, "addKernel launch failed: %s\n", cudaGetErrorString(cudaStatus));
goto Error;
}
// cudaDeviceSynchronize waits for the kernel to finish, and returns
// any errors encountered during the launch.
cudaStatus = cudaDeviceSynchronize();
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaDeviceSynchronize returned error code %d after launching addKernel!\n", cudaStatus);
fprintf(stderr, " %s\n", cudaGetErrorString(cudaStatus));
goto Error;
}
// Copy output vector from GPU buffer to host memory.
cudaStatus = cudaMemcpy(c, dev_c, size * size * sizeof(int), cudaMemcpyDeviceToHost);
if (cudaStatus != cudaSuccess) {
fprintf(stderr, "cudaMemcpy failed!");
goto Error;
}
Error:
cudaFree(dev_c);
cudaFree(dev_a);
cudaFree(dev_b);
return cudaStatus;
}

Answer 1

On Windows, I right clicked the NSight monitor icon in the system tray. There I chose Options>General. We see WDDM TDR delay. It was at 2, and I increased it to 10. Then, I ran my program again, and it worked fine.
This was according to Robert's link (see above)
http://http.developer.nvidia.com/NsightVisualStudio/2.2/Documentation/UserGuide/HTML/Content/Timeout_Detection_Recovery.htm