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"invalid configuration argument " error for the call of CUDA kernel?

Here is my code:

int threadNum = BLOCKDIM/8;
dim3 dimBlock(threadNum,threadNum);
int blocks1 = nWidth/threadNum + (nWidth%threadNum == 0 ? 0 : 1);
int blocks2 = nHeight/threadNum + (nHeight%threadNum == 0 ? 0 : 1);
dim3 dimGrid;
dimGrid.x = blocks1;
dimGrid.y = blocks2;

//  dim3 numThreads2(BLOCKDIM);
//  dim3 numBlocks2(numPixels/BLOCKDIM + (numPixels%BLOCKDIM == 0 ? 0 : 1) );
perform_scaling<<<dimGrid,dimBlock>>>(imageDevice,imageDevice_new,min,max,nWidth, nHeight);
cudaError_t err = cudaGetLastError();
cudasafe(err,"Kernel2");

This is the execution of my second kernel and it is fully independent in term of the usage of data. BLOCKDIM is 512 , nWidth and nHeight are 512 too and cudasafe simply prints the corresponding string message of the error code. This section of the code gives configuration error just after the kernel call.

What might give this error, any idea?

Solution

  • This type of error message frequently refers to the launch configuration parameters (grid/threadblock dimensions in this case, could also be shared memory, etc. in other cases). When you see a message like this it's a good idea just to print out your actual config parameters before launching the kernel, to see if you've made any mistakes.

    You said BLOCKDIM = 512. You have threadNum = BLOCKDIM/8 so threadNum = 64. Your threadblock configuration is:

    dim3 dimBlock(threadNum,threadNum);

    So you are asking to launch blocks of 64 x 64 threads, that is 4096 threads per block. That won't work on any generation of CUDA devices. All current CUDA devices are limited to a maximum of 1024 threads per block, which is the product of the 3 block dimensions.

    Maximum dimensions are listed in a table of the CUDA programming guide, and also available via the deviceQuery CUDA sample code.