Hi,
I am new to CUDA and I have the problem that somehow the kernel doesn’t seem to execute for more than million elements. I’ve tried it also on the simple example from:
__global__
void add(int n, float *x, float *y)
{
for (int i = 0; i < n; i++)
y[i] = x[i] + y[i];
}
int main(void)
{
int N = 1<<20;
float *x, *y;
// Allocate Unified Memory – accessible from CPU or GPU
cudaMallocManaged(&x, N*sizeof(float));
cudaMallocManaged(&y, N*sizeof(float));
// initialize x and y arrays on the host
for (int i = 0; i < N; i++) {
x[i] = 1.0f;
y[i] = 2.0f;
}
// Run kernel on 1M elements on the GPU
add<<<1, 1>>>(N, x, y);
// Wait for GPU to finish before accessing on host
cudaDeviceSynchronize();
// Check for errors (all values should be 3.0f)
float maxError = 0.0f;
for (int i = 0; i < N; i++)
maxError = fmax(maxError, fabs(y[i]-3.0f));
std::cout << "Max error: " << maxError << std::endl;
// Free memory
cudaFree(x);
cudaFree(y);
return 0;
}
If I raise N to more than 1 million, y remains empty. I also checked for an error using cudaGetLastError() but the return value is “cudaSuccess”.
I tested it on two different Systems, both Windows, VS 2015 and not the newest graphics cards: GTX980 and GT755m. On both Systems I have the same problem.
Can someone tell me what limitation is causing this?
Cheers