CUDA kernel stops working when using cooperative groups grid sync() function

Question

I was trying to implement some cuda kernels leveraging the cooperative groups feature when i encountered that the kernel wouldn't do anything at all. I boiled it down to a small example which can be seen below. As soon as i call the sync() function the cuda kernel does not work anymore. I already made sure my GPUs (GTX 1070 Ti) compute capability is high enough and i also added the appropriate switches(-rdc, -gencode) to nvcc.

Compilation command:

nvcc -o kernel.bin kernel.cu -I /nix/store/lxyjz3j1qbrf9hw0nnsdang3gk2a8wpp-cudatoolkit-11.0.3/include/ -ldir /nix/store/lxyjz3j1qbrf9hw0nnsdang3gk2a8wpp-cudatoolkit-11.0.3/nvvm/libdevice/ -L /nix/store/lxyjz3j1qbrf9hw0nnsdang3gk2a8wpp-cudatoolkit-11.0.3/lib/ -L /nix/store/sdjf499xfbykmr3lsyd7084krjxr3mfx-cudatoolkit-11.0.3-lib/lib/ --dont-use-profile -G --std=c++11 -rdc=true -gencode=arch=compute_60,code=sm_60 -lcudadevrt

Kernel without sync()

#include <iostream>
#include <cooperative_groups.h>

using namespace std;

__global__ void coopkernel(float* buffer)
{
    int id = threadIdx.x + blockDim.x * blockIdx.x;
    auto g = cooperative_groups::this_grid();
    buffer[id] = 13;
    // g.sync();
}

Output (just as expected)

Runtime Version: 11000
Driver Version: 11010
Return Code from Kernel: 0
 Explanation: no error
13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13

Kernel FAILING example with sync()

#include <iostream>
#include <cooperative_groups.h>

using namespace std;

__global__ void coopkernel(float* buffer)
{
    int id = threadIdx.x + blockDim.x * threadIdx.y + blockIdx.x*(blockDim.x*blockDim.y);
    auto g = cooperative_groups::this_grid();
    buffer[id] = 13;
    g.sync();
}

Output (everything is 0)


Runtime Version: 11000
Driver Version: 11010
Return Code from Kernel: 0
Explanation: no error
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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Full Code:

#include <iostream>
#include <cooperative_groups.h>

using namespace std;

__global__ void coopkernel(float* buffer)
{
    int id = threadIdx.x + blockDim.x * blockIdx.x;
    auto g = cooperative_groups::this_grid();
    buffer[id] = 13;
    // g.sync();
}

int main()
{
    // Grid with 2 Block in x direction
    dim3 dimGrid(2, 1, 1);

    // 1024 Threads per Block
    dim3 dimBlock(1024, 1, 1);

    int run_version, driver_version;
    cudaRuntimeGetVersion(&run_version);
    cudaDriverGetVersion(&driver_version);

    std::cout << "Runtime Version: ";
    std::cout << run_version;

    std::cout << "\nDriver Version: ";
    std::cout << driver_version;

    // just an arbitrary buffer
    int bytes_buffer = 2048 * sizeof(float);
    float *host_buffer = (float*)malloc(bytes_buffer);

    // initialize to 0
    memset(host_buffer, 0, bytes_buffer);

    // Device pointer to buffer
    float *d_buffer;
    cudaMalloc(&d_buffer, bytes_buffer);
    cudaMemcpy(d_buffer, host_buffer, bytes_buffer, cudaMemcpyHostToDevice);
    
    // Launch kernel
    coopkernel <<<dimGrid,  dimBlock>>> (d_buffer);

    std::cout << "\nReturn Code from Kernel: ";
    std::cout << cudaPeekAtLastError();
    std::cout << "\nExplanation: ";
    std::cout << cudaGetErrorString(cudaGetLastError());
    std::cout << "\n";

    cudaMemcpy(host_buffer, d_buffer, bytes_buffer, cudaMemcpyDeviceToHost);

    // Print the result
    for(int i=0; i < 2048; i++)
    {
        std::cout << host_buffer[i];
        std::cout << ", ";
    }

    cudaFree(d_buffer);
    
    return 0;
}

Questions

Why does this happen ?

How to fix it ?

Or any tips regarding troubleshooting ? It's really weird that kernel returns success via cudaGetLastError() even though it didn't do anything.

P.S nvidia-smi output

nvidia-smi 
Tue Dec  8 18:29:46 2020       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 455.38       Driver Version: 455.38       CUDA Version: 11.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 107...  Off  | 00000000:2A:00.0  On |                  N/A |
|  0%   51C    P0    34W / 180W |   1121MiB /  8116MiB |      1%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1209      G   ...-xorg-server-1.20.8/bin/X      613MiB |
|    0   N/A  N/A      1728      G   ...nt-system/sw/bin/kwin_x11      256MiB |
|    0   N/A  N/A      1772      G   ...ce-5.18.5/bin/plasmashell      119MiB |
|    0   N/A  N/A      1868      G   ...AAAAAAAA== --shared-files       76MiB |
|    0   N/A  N/A      2772      G   ...AAAAAAAAA= --shared-files       48MiB |
+-----------------------------------------------------------------------------+

You cannot use the triple-chevron launch syntax: `<<<...>>>` when launching a cooperative grid kernel. The answer in the linked duplicate explains this and has other recommendations for a proper coop launch, as well. These concepts are covered in [the docs](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#grid-synchronization-cg) as well. — Robert Crovella, Dec 08 '20 at 17:40
simple fix for your code: synchronise the blocks, with auto g = cooperative_groups::this_thread_block(); — geebert, Dec 08 '20 at 17:47
yes but this was just a minimal reproducible example. The stuff i actually use it for is different. — KoKlA, Dec 08 '20 at 20:06
fair enough! If you actually need grid synchronisation, then that obviously is not the solution. — geebert, Dec 08 '20 at 20:09

CUDA kernel stops working when using cooperative groups grid sync() function

Kernel without sync()

Kernel FAILING example with sync()

Questions

0 Answers0