GPU集群RDMA通信技术及拥塞控制

Gui Liang, Siti Norbaya Daud, N. Ismail
{"title":"GPU集群RDMA通信技术及拥塞控制","authors":"Gui Liang, Siti Norbaya Daud, N. Ismail","doi":"10.1145/3603781.3603876","DOIUrl":null,"url":null,"abstract":"Abstract. This paper discusses Remote Direct Memory Access(RDMA) communication technology and the congestion control methods for Graphics Processing Unit(GPU) clusters. The implementation methods of RDMA networks widely used in GPU clusters are studied. Three implementation modes including InfiniBand, iWARP, and RoCE are analysed with comparison of their performance and applicable environments. Then, based on the analysis of a new congestion controls algorithm, DBCC & CBFC algorithm, is proposed. This algorithm based on delay feedback control and credit flow control prevents network congestion or increased latency in GPU cluster RDMA networks. The working principles of the algorithm are introduced including calculating the adjustment amount of the sending rate, initializing the sender and receiver and mechanisms to handle packet loss and timeout. Experimental results show that the algorithm optimizes network performance with RDMA communication in GPU clusters, while avoiding congestion and minimizing packet loss. However, due to the limitation of experimental conditions, it is not possible to conduct more environmental tests. In practical application, the applicability of the algorithm needs to be carefully evaluated and adjusted according to the specific situations.","PeriodicalId":391180,"journal":{"name":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GPU Cluster RDMA communication technology and congestion control\",\"authors\":\"Gui Liang, Siti Norbaya Daud, N. Ismail\",\"doi\":\"10.1145/3603781.3603876\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. This paper discusses Remote Direct Memory Access(RDMA) communication technology and the congestion control methods for Graphics Processing Unit(GPU) clusters. The implementation methods of RDMA networks widely used in GPU clusters are studied. Three implementation modes including InfiniBand, iWARP, and RoCE are analysed with comparison of their performance and applicable environments. Then, based on the analysis of a new congestion controls algorithm, DBCC & CBFC algorithm, is proposed. This algorithm based on delay feedback control and credit flow control prevents network congestion or increased latency in GPU cluster RDMA networks. The working principles of the algorithm are introduced including calculating the adjustment amount of the sending rate, initializing the sender and receiver and mechanisms to handle packet loss and timeout. Experimental results show that the algorithm optimizes network performance with RDMA communication in GPU clusters, while avoiding congestion and minimizing packet loss. However, due to the limitation of experimental conditions, it is not possible to conduct more environmental tests. In practical application, the applicability of the algorithm needs to be carefully evaluated and adjusted according to the specific situations.\",\"PeriodicalId\":391180,\"journal\":{\"name\":\"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3603781.3603876\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3603781.3603876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

摘要本文讨论了图形处理单元(GPU)集群的远程直接内存访问(RDMA)通信技术和拥塞控制方法。研究了GPU集群中广泛应用的RDMA网络的实现方法。分析了InfiniBand、iWARP和RoCE三种实现模式,并对其性能和适用环境进行了比较。然后,在分析拥塞控制算法的基础上,提出了一种新的拥塞控制算法——DBCC & CBFC算法。该算法基于延迟反馈控制和信用流控制,防止了GPU集群RDMA网络中的网络拥塞或延迟增加。介绍了该算法的工作原理,包括计算发送速率调整量、初始化发送端和接收端以及丢包和超时的处理机制。实验结果表明,该算法优化了GPU集群中RDMA通信的网络性能,同时避免了拥塞和最小化了丢包。但是,由于实验条件的限制,不可能进行更多的环境试验。在实际应用中,需要仔细评估算法的适用性,并根据具体情况进行调整。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU Cluster RDMA communication technology and congestion control
Abstract. This paper discusses Remote Direct Memory Access(RDMA) communication technology and the congestion control methods for Graphics Processing Unit(GPU) clusters. The implementation methods of RDMA networks widely used in GPU clusters are studied. Three implementation modes including InfiniBand, iWARP, and RoCE are analysed with comparison of their performance and applicable environments. Then, based on the analysis of a new congestion controls algorithm, DBCC & CBFC algorithm, is proposed. This algorithm based on delay feedback control and credit flow control prevents network congestion or increased latency in GPU cluster RDMA networks. The working principles of the algorithm are introduced including calculating the adjustment amount of the sending rate, initializing the sender and receiver and mechanisms to handle packet loss and timeout. Experimental results show that the algorithm optimizes network performance with RDMA communication in GPU clusters, while avoiding congestion and minimizing packet loss. However, due to the limitation of experimental conditions, it is not possible to conduct more environmental tests. In practical application, the applicability of the algorithm needs to be carefully evaluated and adjusted according to the specific situations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信