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 |
+-----------------------------------------------------------------------------+