CUDA并行规约(相邻配对-优化)

来源:互联网 发布:锐速破解版 windows 编辑:程序博客网 时间:2024/06/01 10:30

前文CUDA的并行规约算法的示意图如下,分析可知,相邻之间的线程执行不同的路径,存在线程束分化。



为了使得线程束不存在分化,每个warp(32个线程)执行同一指令,可调整相邻的线程的数组索引实现优化。示意图如下图所示,数组的存储位置没变,只是没个线程执行的数组发生了变化,这样的处理模式可以降低相邻线程分化降低,尽早释放后面的线程。



实验在GTX1050Ti进行,线程块长度为1024,性能提升1.73倍左右,但随着线程块的减少,性能提升也有所降低,这主要和warp size有关~.代码如下:

#include "cuda_runtime.h"#include "device_launch_parameters.h"#include <stdio.h>#include "math.h"#include "stdlib.h"//错误检查的宏定义#define CHECK(call)\{\const cudaError_t status=call;\if (status!=cudaSuccess)\{\printf("文件:%s,函数:%s,行号:%d",__FILE__,\__FUNCTION__,__LINE__);\printf("%s", cudaGetErrorString(status));\exit(1);\}\}\//核函数__global__ void Kernel(int *d_data, int *d_local_sum, int N){int tid = threadIdx.x;int index = blockIdx.x*blockDim.x + threadIdx.x;int *data = d_data + blockIdx.x*blockDim.x;if (index >= N) return;for (int strize = 1; strize < blockDim.x; strize *= 2){int idx = tid*strize * 2;if (idx < blockDim.x)data[idx]+= data[idx+strize];__syncthreads();}if (tid == 0){d_local_sum[blockIdx.x] = data[0];}}//主函数int main(){//基本参数设置cudaSetDevice(0);const int N = 65536;int local_length =1024;int total_sum = 0;dim3 grid(((N + local_length - 1) / local_length), 1);dim3 block(local_length, 1);int *h_data = nullptr;int *h_local_sum = nullptr;int *d_data = nullptr;int *d_local_sum = nullptr;//Host&Deivce内存申请及数组初始化h_data = (int*)malloc(N * sizeof(int));h_local_sum = (int*)malloc(int(grid.x) * sizeof(int));CHECK(cudaMalloc((void**)&d_data, N * sizeof(int)));CHECK(cudaMalloc((void**)&d_local_sum, int(grid.x) * sizeof(int)));for (int i = 0; i < N; i++)h_data[i] = int(10 * sin(0.02*3.14*i));//限制数组元素值,防止最终求和值超过int的范围//数据拷贝至DeviceCHECK(cudaMemcpy(d_data, h_data, N * sizeof(int), cudaMemcpyHostToDevice));//for (int i=0;i<200;i++)//执行核函数Kernel << <grid, block >> > (d_data, d_local_sum, N);//数据拷贝至HostCHECK(cudaMemcpy(h_local_sum, d_local_sum, int(grid.x) * sizeof(int),cudaMemcpyDeviceToHost));//同步&重置设备CHECK(cudaDeviceSynchronize());CHECK(cudaDeviceReset());for (int i = 0; i < int(grid.x); i++){total_sum += h_local_sum[i];}printf("%d \n", total_sum);//getchar();return 0;}




原创粉丝点击