On Scalability for MPI Runtime Systems

G. Bosilca, T. Hérault, Ala Rezmerita, Jack J. Dongarra
{"title":"On Scalability for MPI Runtime Systems","authors":"G. Bosilca, T. Hérault, Ala Rezmerita, Jack J. Dongarra","doi":"10.1109/CLUSTER.2011.29","DOIUrl":null,"url":null,"abstract":"The future of high performance computing, as being currently foretold, will gravitate toward hundreds of thousands to million node machines, harnessing the computing power of billions of cores. While the hardware part is well covered, the software infrastructure at that scale is vague. However, no matter what the infrastructure will be, efficiently running parallel applications on such large machines will require optimized runtime environments that are scalable and resilient. More particularly, considering a future where Message Passing Interface (MPI) remains a major programming paradigm, the MPI implementations will have to seamlessly adapt to launching and managing large scale applications on resources several levels of magnitude larger than today. In this paper, we present a modified version of the Open MPI runtime that has been adapted towards a scalability goal. We evaluate the performance and compare it with two widely used runtime systems: the default version of Open MPI and MPICH2; using various underlying launching systems. The performance evaluation demonstrates a significant improvement over the state of the art. We also discuss the basic requirements for an exascale-ready parallel runtime.","PeriodicalId":200830,"journal":{"name":"2011 IEEE International Conference on Cluster Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLUSTER.2011.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

The future of high performance computing, as being currently foretold, will gravitate toward hundreds of thousands to million node machines, harnessing the computing power of billions of cores. While the hardware part is well covered, the software infrastructure at that scale is vague. However, no matter what the infrastructure will be, efficiently running parallel applications on such large machines will require optimized runtime environments that are scalable and resilient. More particularly, considering a future where Message Passing Interface (MPI) remains a major programming paradigm, the MPI implementations will have to seamlessly adapt to launching and managing large scale applications on resources several levels of magnitude larger than today. In this paper, we present a modified version of the Open MPI runtime that has been adapted towards a scalability goal. We evaluate the performance and compare it with two widely used runtime systems: the default version of Open MPI and MPICH2; using various underlying launching systems. The performance evaluation demonstrates a significant improvement over the state of the art. We also discuss the basic requirements for an exascale-ready parallel runtime.
关于MPI运行时系统的可伸缩性
正如目前预测的那样,高性能计算的未来将倾向于数十万到数百万个节点的机器,利用数十亿个核心的计算能力。虽然硬件部分被很好地覆盖了,但这种规模的软件基础设施是模糊的。然而,无论基础设施是什么,在如此大的机器上有效地运行并行应用程序都需要优化的可伸缩和弹性运行时环境。更具体地说,考虑到未来消息传递接口(Message Passing Interface, MPI)仍然是主要的编程范例,MPI实现必须无缝地适应在比现在大几个量级的资源上启动和管理大规模应用程序。在本文中,我们提出了一个修改版本的Open MPI运行时,它已经适应了可伸缩性的目标。我们评估了性能,并将其与两种广泛使用的运行时系统进行了比较:默认版本的Open MPI和MPICH2;使用各种底层发射系统。性能评估显示了对当前技术水平的重大改进。我们还讨论了百亿亿级并行运行时的基本要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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