我是CUDA的新手，一般来说是算法。有人能告诉我，如果我这样做是正确的，或者如果有一个更好的方法来做到这一点。一个问题是代码的输入和输出应该在GPU上，这样主机和设备之间就没有内存复制。

#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#include <stdio.h>
#include <stdint.h>

#include <iostream>

#define TILE_WIDTH 8

__global__ void gpu_sumElements(int height, int width, float *in, float *out){

    extern __shared__ float cache[];

    int w = blockIdx.x * blockDim.x + threadIdx.x; // Col // width
    int h = blockIdx.y * blockDim.y + threadIdx.y;

    int index = h * width + w;
    int cacheIndex = threadIdx.y * blockDim.x + threadIdx.x;

    float temp = 0;

    if ((w < width) && (h < height)){
        temp += in[index];
        //index += (height * width);
    }

    cache[cacheIndex] = temp;
    __syncthreads();

    int i = (blockDim.x * blockDim.y) / 2;
    while (i != 0){
        if (cacheIndex < i)
            cache[cacheIndex] += cache[cacheIndex + i];
        __syncthreads();
        i /= 2;
    }

    if (cacheIndex == 0)
        out[blockIdx.y * gridDim.x + blockIdx.x] = cache[0];
}

int main(){
                                                                        // Initial Parameters       
    int width = 2363;
    int height = 781;
    float my_sum = 0;

    int block_height = (height - 1) / TILE_WIDTH + 1;
    int block_width = (width - 1) / TILE_WIDTH + 1;

    dim3 dimGrid(block_width, block_height, 1);
    dim3 dimBlock(TILE_WIDTH, TILE_WIDTH, 1);

    int sharedMemSize = TILE_WIDTH * TILE_WIDTH * sizeof(float);
                                                                        // Initialize host arrays
    float *test_array = new float[height * width];
    float *out = new float[height * width];
    for (int i = 0; i < (height * width); i++)
        test_array[i] = 1.0f;
                                                                        // Initialize device arrays 
    float *gpu_temp_array;
    float *gpu_out;
    cudaMalloc((void **)&gpu_temp_array, (height * width * sizeof(float)));
    cudaMalloc((void **)&gpu_out, (height * width * sizeof(float)));
    cudaMemcpy(gpu_out, test_array, (height * width * sizeof(float)), cudaMemcpyHostToDevice);

                                                                        // Copy these, need them elsewhere
    float sum_height = height; 
    float sum_width = width ;
    dim3 sum_dimGrid = dimGrid;
    int i = (height * width); 

                                                                        // Launch kernel, get & print results
    while (i != 0){
        gpu_sumElements<<<sum_dimGrid, dimBlock, sharedMemSize>>>(sum_height, sum_width, gpu_out, gpu_temp_array);
        cudaMemcpy(gpu_out, gpu_temp_array, (sum_height * sum_width * sizeof(float)), cudaMemcpyDeviceToDevice);
        cudaMemset(gpu_temp_array, 0, (height * width * sizeof(float)));

        sum_height = ceil(sum_height/TILE_WIDTH);
        sum_width = ceil(sum_width/TILE_WIDTH);;
        sum_dimGrid.x = (sum_width - 1) / TILE_WIDTH + 1; 
        sum_dimGrid.y = (sum_height - 1) / TILE_WIDTH + 1;
        i /= TILE_WIDTH*TILE_WIDTH;
    }

    cudaMemcpy(out, gpu_out, (height * width * sizeof(float)), cudaMemcpyDeviceToHost);
    std::cout << out[0] << std::endl << std::endl;  

    delete[] test_array;
    delete[] out;
    cudaFree(gpu_out);
    cudaFree(gpu_temp_array);

    system("pause");
    return 0;
}