How File-access Patterns Influence the Degree of I/O Interference between Cluster Applications

A. Shah, C. Kuo, Akihiro Nomura, S. Matsuoka, F. Wolf
{"title":"How File-access Patterns Influence the Degree of I/O Interference between Cluster Applications","authors":"A. Shah, C. Kuo, Akihiro Nomura, S. Matsuoka, F. Wolf","doi":"10.14529/JSFI190203","DOIUrl":null,"url":null,"abstract":"On large-scale clusters, tens to hundreds of applications can simultaneously access a parallel file system, leading to contention and, in its wake, to degraded application performance. In this article, we analyze the influence of file-access patterns on the degree of interference. As it is by experience most intrusive, we focus our attention on write-write contention. We observe considerable differences among the interference potentials of several typical write patterns. In particular, we found that if one parallel program writes large output files while another one writes small checkpointing files, then the latter is slowed down when the checkpointing files are small enough and the former is vice versa. Moreover, applications with a few processes writing large output files already can significantly hinder applications with many processes from checkpointing small files. Such effects can seriously impact the runtime of real applications—up to a factor of five in one instance. Our insights and measurement techniques offer an opportunity to automatically classify the interference potential between applications and to adjust scheduling decisions accordingly.","PeriodicalId":338883,"journal":{"name":"Supercomput. Front. Innov.","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Supercomput. Front. Innov.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14529/JSFI190203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

On large-scale clusters, tens to hundreds of applications can simultaneously access a parallel file system, leading to contention and, in its wake, to degraded application performance. In this article, we analyze the influence of file-access patterns on the degree of interference. As it is by experience most intrusive, we focus our attention on write-write contention. We observe considerable differences among the interference potentials of several typical write patterns. In particular, we found that if one parallel program writes large output files while another one writes small checkpointing files, then the latter is slowed down when the checkpointing files are small enough and the former is vice versa. Moreover, applications with a few processes writing large output files already can significantly hinder applications with many processes from checkpointing small files. Such effects can seriously impact the runtime of real applications—up to a factor of five in one instance. Our insights and measurement techniques offer an opportunity to automatically classify the interference potential between applications and to adjust scheduling decisions accordingly.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
文件访问模式如何影响集群应用程序之间的I/O干扰程度
在大规模集群上,数十到数百个应用程序可以同时访问一个并行文件系统,这会导致争用,进而降低应用程序性能。在本文中,我们分析了文件访问模式对干扰程度的影响。根据经验,它是最具侵入性的,因此我们将注意力集中在写-写争用上。我们观察到几种典型写入模式的干扰电位之间存在相当大的差异。特别是,我们发现,如果一个并行程序写大的输出文件,而另一个程序写小的检查点文件,那么当检查点文件足够小时,后者的速度会减慢,而前者反之亦然。此外,使用少数进程编写大型输出文件的应用程序已经严重阻碍了使用许多进程检查小文件的应用程序。这样的影响可能会严重影响实际应用程序的运行时,在一个实例中影响可达5倍。我们的见解和测量技术提供了一个机会,可以自动对应用程序之间的潜在干扰进行分类,并相应地调整调度决策。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Supercomputer-Based Modeling System for Short-Term Prediction of Urban Surface Air Quality River Routing in the INM RAS-MSU Land Surface Model: Numerical Scheme and Parallel Implementation on Hybrid Supercomputers Data Assimilation by Neural Network for Ocean Circulation: Parallel Implementation Multistage Iterative Method to Tackle Inverse Problems of Wave Tomography Machine Learning Approaches to Extreme Weather Events Forecast in Urban Areas: Challenges and Initial Results
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1