当我遇到内核根本不会做任何事情时，我试图利用协作组功能实现一些 cuda 内核。我把它归结为一个小例子，如下所示。一旦我调用该sync()函数，cuda 内核就不再工作了。我已经确保我的 GPU（GTX 1070 Ti）计算能力足够高，并且我还在 nvcc 中添加了适当的开关（-rdc、-gencode）。
编译命令：
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
没有同步（）的内核
#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();
}
输出（正如预期的那样）
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
带有 sync() 的内核失败示例
#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();
}
输出（全部为 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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完整代码：
#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;
}
问题
为什么会这样？
如何解决？
或有关故障排除的任何提示？cudaGetLastError()即使内核没有做任何事情，内核也会通过它返回成功，这真的很奇怪。
PS nvidia-smi 输出
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 |
+-----------------------------------------------------------------------------+