写一段用cuda执行的基于形状的模板匹配代码

以下是一个基于形状的模板匹配代码示例，使用CUDA加速执行：

#include <cuda_runtime.h>
#include <device_launch_parameters.h>
#include <stdio.h>

// 定义常量，指定线程块大小
#define BLOCK_SIZE 32

// CUDA核函数，用于计算匹配得分
__global__ void templateMatching(const float *input, const float *template, float *output,
    int inputWidth, int inputHeight, int templateWidth, int templateHeight)
{
    int x = blockIdx.x * blockDim.x + threadIdx.x;
    int y = blockIdx.y * blockDim.y + threadIdx.y;

    if (x >= inputWidth || y >= inputHeight) return;

    float sum = 0.0f;

    // 计算模板与输入图像的匹配得分
    for (int i = 0; i < templateHeight; i++) {
        for (int j = 0; j < templateWidth; j++) {
            int inputIndex = (y + i) * inputWidth + (x + j);
            int templateIndex = i * templateWidth + j;
            float diff = input[inputIndex] - template[templateIndex];
            sum += diff * diff;
        }
    }

    output[y * inputWidth + x] = sum;
}

int main()
{
    // 定义输入图像和模板
    float input[] = {
        1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f,
        7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f,
        13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f,
        19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f,
        25.0f, 26.0f, 27.0f, 28.0f, 29.0f, 30.0f,
        31.0f, 32.0f, 33.0f, 34.0f, 35.0f, 36.0f
    };
    float template[] = {
        8.0f, 9.0f, 10.0f,
        14.0f, 15.0f, 16.0f,
        20.0f, 21.0f, 22.0f
    };
    int inputWidth = 6, inputHeight = 6;
    int templateWidth = 3, templateHeight = 3;

    // 计算输出数组大小并分配CUDA内存
    int outputSize = inputWidth * inputHeight * sizeof(float);
    float *d_input, *d_template, *d_output;
    cudaMalloc((void **)&d_input, inputWidth * inputHeight * sizeof(float));
    cudaMalloc((void **)&d_template, templateWidth * templateHeight * sizeof(float));
    cudaMalloc((void **)&d_output, outputSize);

    // 将输入数据复制到CUDA设备
    cudaMemcpy(d_input, input, inputWidth * inputHeight * sizeof(float), cudaMemcpyHostToDevice);
    cudaMemcpy(d_template, template, templateWidth * templateHeight * sizeof