用了一周多的时间,终于能看懂并且会用distributed data parallel (DDP),来感受下不同条件下的 LeNet-Mnist 的运算速度。data parallel 简称 DP,distributed data parallel 简称 DDP。 Data parallel(DP) 和 Distributed Data parallel (DDP)的区别 DDP 支持模型并行,当模型太大时,可按照网络拆分模型到两个或者多个...
importosfromdatetimeimportdatetimeimportargparseimporttorch.multiprocessingasmpimporttorchvisionimporttorchvision.transformsastransformsimporttorchimporttorch.nnasnnimporttorch.distributedasdistfromapex.parallelimportDistributedDataParallelasDDPfromapeximportamp 之后,我们训练了一个MNIST分类的简单卷积网络 classConvNet(nn.Modu...
与DataParallel不同的是,Distributed Data Parallel会开设多个进程而非线程,进程数 = GPU数,每个进程都可以独立进行训练,也就是说代码的所有部分都会被每个进程同步调用,如果你某个地方print张量,你会发现device的差异
为了解决这个问题,PyTorch提供了Distributed Data Parallel(DDP)这种技术,它允许多个GPU并行处理数据,从而显著加速模型训练。 一、Distributed Data Parallel简介 Distributed Data Parallel(DDP)是PyTorch中的一种并行训练技术,它允许多个GPU协同工作,共同处理数据,以加速模型的训练。在DDP中,每个GPU都维护一个完整的模型副本...
import torch.distributed as dist import torch.multiprocessing as mp import torch.nn as nn import torch.optim as optim from torch.nn.parallel import DistributedDataParallel as DDP def example(rank, world_size): # 创建进程组 dist.init_process_group("gloo", rank=rank, world_size=world_size) ...
Forward pass in distributed model parallel If we take the usual quadratic loss function, then the forward pass finally computes the value of the lossL: Loss computation in distributed data parallel Note that at line (3), the two termsL₁andL₂only depends on a single, but different data...
CMU Database Systems - Parallel Execution 并发执行,主要为了增大吞吐,降低延迟,提高数据库的可用性 先区分一组概念,parallel和distributed的区别 总的来说,parallel是指在物理上很近的节点,比如本机的多个线程或进程,不用考虑通信代价 distributed,要充分的考虑通信代价,failover的问题,更为复杂...
Data parallel kernel “parallel_for” Go to Code Walkthrough 2. Unified Shared Memory (USM) The Mandelbrot Set is a program that demonstrates oneAPI concepts and functionally using the SYCL programming language. You will learn about: Unified shared memory Managing and accessing memory Parallel impl...
Parallel.For 首先先写一个普通的循环: privatevoidNormalFor() { for(var i=0; i<10000; i++) { for(var j=0; j<1000; j++) { for(var k=0; k<100; k++) { DoSomething(); } } } } 再看一个并行的For语句: privatevoidParallelFor() ...
Fully Sharded Data Parallel (FSDP) makes training larger, more advanced AI models more efficiently than ever using fewer GPUs.