常见处理器有哪些硬件加速功能？

常见的处理器有各自独有的硬件加速功能，下面列举一些常见的处理器及其对应的硬件加速功能：

1. NVIDIA GPU：NVIDIA GPU拥有丰富的加速功能，包括CUDA加速、NVIDIA Tensor Cores加速、Ray-tracing加速等。其中，CUDA加速可以使用NVIDIA CUDA Toolkit进行编程，下面是一个使用CUDA进行矩阵相乘的示例代码：

#include <stdio.h>

// CUDA Kernel function to add elements of two matrices
__global__
void matrixAddKernel(int n, float* a, float* b, float* c)
{
    int i = blockIdx.x*blockDim.x + threadIdx.x;
    if (i < n*n)
        c[i] = a[i] + b[i];
}

// main function
int main()
{
    int n = 1024;
    float *a, *b, *c;  // host copies of a, b, c
    float *d_a, *d_b, *d_c;  // device copies of a, b, c
    int size = n*n*sizeof(float);
    cudaError_t err;
    // Allocate space for device copies of a, b, c
    err = cudaMalloc((void **)&d_a, size);
    if (err != cudaSuccess) printf("%s\n", cudaGetErrorString(err));
    err = cudaMalloc((void **)&d_b, size);
    if (err != cudaSuccess) printf("%s\n", cudaGetErrorString(err));
    err = cudaMalloc((void **)&d_c, size);
    if (err != cudaSuccess) printf("%s\n", cudaGetErrorString(err));
    // Allocate space for host copies of a, b, c and setup input values
    a = (float *)malloc(size);
    b = (float *)malloc(size);
    c = (float *)malloc(size);
    for (int i = 0; i < n*n; ++i)
    {
        a[i] = i;
        b[i] = i;
    }
    // Copy inputs to device