Cuda failed to run on blocks but ok on grids - cuda

Question

Here is part of my cuda code from cs344:
It is a task to convert a picture in rgb to gray.
The code runs ok now.
But when I use the code in the comments. It fails.
__global__
void rgba_to_greyscale(const uchar4* const rgbaImage,
unsigned char* const greyImage,
int numRows, int numCols)
{
//int x = threadIdx.x ;
//int y = threadIdx.y ;
int x = blockIdx.x ;
int y = blockIdx.y ;
if (x<numCols && y<numRows)
{
uchar4 rgba = rgbaImage[y*numCols+x] ;
float channelSum = .299f * rgba.x + .587f * rgba.y + .114f * rgba.z;
greyImage[y*numCols+x] = channelSum;
}
}
void your_rgba_to_greyscale(const uchar4 * const h_rgbaImage,
uchar4 * const d_rgbaImage, unsigned char* const d_greyImage,
size_t numRows, size_t numCols)
{
// const dim3 blockSize(numCols,numRows , 1); //TODO
// const dim3 gridSize( 1, 1, 1); //TODO
const dim3 blockSize(1,1 , 1); //TODO
const dim3 gridSize( numCols,numRows , 1); //TODO
std::cout << numCols << " " << numRows << std::endl ; // numCols=557 numRows=313
rgba_to_greyscale<<<gridSize, blockSize>>>(d_rgbaImage, d_greyImage, numRows, numCols);
cudaDeviceSynchronize();
checkCudaErrors(cudaGetLastError());
}
The code fails to run when I use the commented ones, with errors:
CUDA error at: /home/yc/cuda_prj/cs344_bak/Problem Sets/Problem Set 1/student_func.cu:90
invalid configuration argument cudaGetLastError()
Here is my deviceQuery report:
Detected 1 CUDA Capable device(s)
Device 0: "GeForce GTX 1080"
CUDA Driver Version / Runtime Version 8.0 / 8.0
CUDA Capability Major/Minor version number: 6.1
Total amount of global memory: 8110 MBytes (8504279040 bytes)
(20) Multiprocessors, (128) CUDA Cores/MP: 2560 CUDA Cores
GPU Max Clock rate: 1823 MHz (1.82 GHz)
Memory Clock rate: 5005 Mhz
Memory Bus Width: 256-bit
L2 Cache Size: 2097152 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 1 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GTX 1080
Can anyone tell me why?

Answer 1

Robert posts the answer that solves the problem:
The total threads per block is the product of the dimensions. If your dimensions are numCols=557 numRows=313 then the product of those is over 150,000. The limit on the total threads per block on your device is 1024 and it is in the deviceQuery output here: Maximum number of threads per block: 1024