CUDA:将设备函数作为参数传递给全局函数

CUDA: Pass device function as an argument to global function

如何制作这样的作品?

#define Eval(x, y, func) {y = func(x);}
__global__ void Evaluate(double *xs, double *ys, int N, double f(double))
{
    int tid = threadIdx.x;
    if (tid < N)
        Eval(xs[tid], ys[tid], f);
        
    
}

然后在主函数里面我有

    double *xs_d, *ys_d;
    double *xs_h, *ys_h;
    xs_h = (double *) malloc(sizeof(double) * 256);
    ys_h = (double *) malloc(sizeof(double) * 256);
    cudaMalloc((void **)&xs_d, sizeof(double) * 256);
    cudaMalloc((void **)&ys_d, sizeof(double) * 256);
    for (int i = 0; i < 256; i++)
    {
        xs_h[i] = (double)i;
    }
    HANDLE_ERROR(cudaMemcpy(xs_d, xs_h, 256*sizeof(double), cudaMemcpyHostToDevice));
    Evaluate<<<1,256>>>(xs_d, ys_d, 256, Sin);
    cudaDeviceSynchronize();
    HANDLE_ERROR(cudaMemcpy(ys_h, ys_d, 256*sizeof(double), cudaMemcpyDeviceToHost));

最后一行失败。到目前为止,我已经看到了这样的解决方案 How to pass device function as an input argument to host-side function? 但它们使用了 __device__ 函数,主机无法更改或访问这些函数(例如 main )函数。例如,我不能将 __device__ int *fptrf1 = (int *)f1;(取自示例)放在 main 中。是否有可能以某种方式具有这种灵活性?

For example, I cannot put __device__ int *fptrf1 = (int *)f1; (taken from the example) inside main. Is it possible to somehow have this flexibility?

一种可能的方法是使用 lambda:

$ cat t151.cu
#define Eval(x, y, func) {y = func(x);}
template <typename F>
__global__ void Evaluate(double *xs, double *ys, int N, F f)
{
    int tid = threadIdx.x;
    if (tid < N)
        Eval(xs[tid], ys[tid], f);


}

int main(){
    double *xs_d, *ys_d;
    double *xs_h, *ys_h;
    xs_h = (double *) malloc(sizeof(double) * 256);
    ys_h = (double *) malloc(sizeof(double) * 256);
    cudaMalloc((void **)&xs_d, sizeof(double) * 256);
    cudaMalloc((void **)&ys_d, sizeof(double) * 256);
    for (int i = 0; i < 256; i++)
    {
        xs_h[i] = (double)i;
    }

    cudaMemcpy(xs_d, xs_h, 256*sizeof(double), cudaMemcpyHostToDevice);
    auto Sinlambda = [] __host__ __device__ (double v) {return sin(v);};
    Evaluate<<<1,256>>>(xs_d, ys_d, 256, Sinlambda);
    cudaDeviceSynchronize();
    cudaMemcpy(ys_h, ys_d, 256*sizeof(double), cudaMemcpyDeviceToHost);
}
$ nvcc -o t151 t151.cu -std=c++11 --extended-lambda
$ cuda-memcheck ./t151
========= CUDA-MEMCHECK
========= ERROR SUMMARY: 0 errors
$

(CUDA 11.3)

对于各种设备函数指针的使用,此 链接到许多示例。