最开始不能理解,因为认为数据经过shared memory多出一层开销,为什么速度反而会变快呢,后来参考英伟达官方论坛的解释: why copy using shared memory is faster than direct copyforums.developer.nvidia.com/t/why-copy-using-shared-memory-is-faster-than-direct-copy/70257/3 通过shared memory,使得对DRAM的loa...
用nsys 测得copyRow的平均运行时间为157423.7ns。 最开始不能理解,因为认为数据经过shared memory多出一层开销,为什么速度反而会变快呢,后来参考英伟达官方论坛的解释: forums.developer.nvidia.com/t/why-copy-using-shared-memory-is-faster-than-direct-copy/70257/3 通过shared memory,使得对DRAM的load和store分开...
This code reverses the data in a 64-element array using shared memory. The two kernels are very similar, differing only in how the shared memory arrays are declared and how the kernels are invoked. Static Shared Memory If the shared memory array size is known at compile time, as in the ...
Q: How can I find out how many registers / how much shared/constant memory my kernel is using? Add the option "--ptxas-options=-v" to the nvcc command line. When compiling, this information will be output to the console.Q: Is it possible to execute multiple kernels at the same ...
#pragmaonce#include"cuda_runtime.h"#include"device_launch_parameters.h"#include"device_functions.h"#include<iostream>usingnamespacestd;constintNX =10240;//数组长度constintThreadX =256;//线程块大小//使用shared memory和多个线程块__global__voidd_SharedMemoryTest(double*para) ...
共享内存(shared memory)是位于SM上的on-chip(片上)一块内存,每个SM都有,就是内存比较小,早期的GPU只有16K(16384),现在生产的GPU一般都是48K(49152)。 共享内存由于是片上内存,因而带宽高,延迟小(较全局内存而言),合理使用共享内存对程序效率具有很大提升。
(&d_x,M));printf("\nUsing global memory only:\n");timing(h_x,d_x,0);printf("\nUsing static shared memory:\n");timing(h_x,d_x,1);printf("\nUsing dynamic shared memory:\n");timing(h_x,d_x,2);free(h_x);CHECK(cudaFree(d_x));return0;}void__global__reduce_global(...
block:每个线程块(block)内都有自己的shared memory(共享内存),所有线程块内的所有线程共享这段内存资源 grid:每个grid都有自己的global memory(全局内存),constant memory(常量内存)和texture memory(纹理内存),不同线程块的线程都可使用。其中常量内存和纹理内存为只读内存空间。
// using ILP 2 to improve the performance __global__ void matrixMulSharedILPkernel(float* A, float* B, float* C, int width){ int row = blockIdx.y * blockDim.y * 2 + threadIdx.y; int col = blockIdx.x * blockDim.x + threadIdx.x; float val[2] = {0.0f}; __shared__ ...
is composed of applying a series of filters to the image. After reading this guide, you’ll be able to efficiently apply filters to images using shared memory of CUDA architecture. Here’s a step by step guide to write your own filter of any type and size. For simplicity I’ll use a...