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...
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) # ...
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...
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
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...
第二:开多个进程,一个进程运行在一张卡上,每个进程负责一部分数据。总结:单机/多机-多进程,通过torch.nn.parallel.DistributedDataParallel实现。 毫无疑问,第一种简单,第二种复杂,毕竟 进程间 通信比较复杂。 torch.nn.DataParallel和torch.nn.parallel.DistributedDataParallel,下面简称为DP和DDP。
(especially at this moment of time) of having multiple GPUs, you are likely to find Distributed Data Parallel (DDP) helpful in terms of model training. DDP performs model training across multiple GPUs, in a transparent fashion. You can have multiple GPUs on a single machine, or mult...
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...
The SageMaker AI distributed data parallelism (SMDDP) library is a collective communication library and improves compute performance of distributed data parallel training.