A Comparative Study of the NAS MG Benchmark across Parallel Languages and Architectures

B. Chamberlain, Steven J. Deitz, L. Snyder
{"title":"A Comparative Study of the NAS MG Benchmark across Parallel Languages and Architectures","authors":"B. Chamberlain, Steven J. Deitz, L. Snyder","doi":"10.1109/SC.2000.10006","DOIUrl":null,"url":null,"abstract":"Hierarchical algorithms such as multigrid applications form an important cornerstone for scientific computing. In this study, we take a first step toward evaluating parallel language support for hierarchical applications by comparing implementations of the NAS MG benchmark in several parallel programming languages: Co-Array Fortran, High Performance Fortran, Single Assignment C, and ZPL. We evaluate each language in terms of its portability, its performance, and its ability to express the algorithm clearly and concisely. Experimental platforms include the Cray T3E, IBM SP, SGI Origin, Sun Enterprise 5500, and a high-performance Linux cluster. Our findings indicate that while it is possible to achieve good portability, performance, and expressiveness, most languages currently fall short in at least one of these areas. We find a strong correlation between expressiveness and a language’s support for a global view of computation, and we identify key factors for achieving portable performance in multigrid applications.","PeriodicalId":228250,"journal":{"name":"ACM/IEEE SC 2000 Conference (SC'00)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"60","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM/IEEE SC 2000 Conference (SC'00)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.2000.10006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 60

Abstract

Hierarchical algorithms such as multigrid applications form an important cornerstone for scientific computing. In this study, we take a first step toward evaluating parallel language support for hierarchical applications by comparing implementations of the NAS MG benchmark in several parallel programming languages: Co-Array Fortran, High Performance Fortran, Single Assignment C, and ZPL. We evaluate each language in terms of its portability, its performance, and its ability to express the algorithm clearly and concisely. Experimental platforms include the Cray T3E, IBM SP, SGI Origin, Sun Enterprise 5500, and a high-performance Linux cluster. Our findings indicate that while it is possible to achieve good portability, performance, and expressiveness, most languages currently fall short in at least one of these areas. We find a strong correlation between expressiveness and a language’s support for a global view of computation, and we identify key factors for achieving portable performance in multigrid applications.
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
跨并行语言和体系结构的NAS MG基准比较研究
分层算法如多网格应用构成了科学计算的重要基石。在这项研究中,我们通过比较几种并行编程语言(Co-Array Fortran、High Performance Fortran、Single Assignment C和ZPL)对NAS MG基准的实现,迈出了评估并行语言对分层应用程序支持的第一步。我们根据可移植性、性能以及清晰简洁地表达算法的能力来评估每种语言。实验平台包括Cray T3E、IBM SP、SGI Origin、Sun Enterprise 5500和一个高性能Linux集群。我们的研究结果表明,虽然有可能实现良好的可移植性、性能和表达性,但大多数语言目前至少在这些领域中的一个方面存在不足。我们发现表达性和语言对计算全局视图的支持之间存在很强的相关性,并且我们确定了在多网格应用程序中实现可移植性能的关键因素。
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
An Object-Oriented Job Execution Environment Automatically Tuned Collective Communications Architectural and Performance Evaluation of GigaNet and Myrinet Interconnects on Clusters of Small-Scale SMP Servers Parallel Smoothed Aggregation Multigrid : Aggregation Strategies on Massively Parallel Machines High-Cost CFD on a Low-Cost Cluster
×
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