2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)最新文献

筛选

英文中文

Parallel OpenMP and OpenACC Mixing Layer Simulation 并行OpenMP和OpenACC混合层仿真

2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP) Pub Date : 2022-03-01 DOI: 10.1109/pdp55904.2022.00036

H. Silva, C. Schepke, Natiele Lucca, C. Cristaldo, Dalmo Paim de Oliveira

引用次数: 2

Accelerating Distributed Deep Reinforcement Learning by In-Network Experience Sampling 利用网络内经验采样加速分布式深度强化学习

2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP) Pub Date : 2021-10-26 DOI: 10.1109/pdp55904.2022.00020

Masaki Furukawa, Hiroki Matsutani

{"title":"Accelerating Distributed Deep Reinforcement Learning by In-Network Experience Sampling","authors":"Masaki Furukawa, Hiroki Matsutani","doi":"10.1109/pdp55904.2022.00020","DOIUrl":"https://doi.org/10.1109/pdp55904.2022.00020","url":null,"abstract":"A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning based on DQN (Deep Q-Network). In distributed reinforcement learning, Actor nodes acquire experiences by interacting with a given environment and a Learner node optimizes their DQN model. Since data transfer between Actor and Learner nodes increases depending on the number of Actor nodes and their experience size, communication overhead between them is one of major performance bottlenecks. In this paper, their communication performance is optimized by using DPDK (Data Plane Development Kit). Specifically, DPDK-based low-latency experience replay memory server is deployed between Actor and Learner nodes interconnected with a 40GbE (40Gbit Ethernet) network. Evaluation results show that, as a network optimization technique, kernel bypassing by DPDK reduces network access latencies to a shared memory server by 32.7% to 58.9%. As another network optimization technique, an in-network experience replay memory server between Actor and Learner nodes reduces access latencies to the experience replay memory by 11.7% to 28.1% and communication latencies for prioritized experience sampling by 21.9% to 29.1%.","PeriodicalId":210759,"journal":{"name":"2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122317103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

首页上一页