Run-time recognition of task parallelism within the P++ parallel array class library

R. Parsons, D. Quinlan
{"title":"Run-time recognition of task parallelism within the P++ parallel array class library","authors":"R. Parsons, D. Quinlan","doi":"10.1109/SPLC.1993.365580","DOIUrl":null,"url":null,"abstract":"This paper explores the use of a run-time system to recognize task parallelism within a C++ array class library. Run-time systems currently support data parallelism in P++, FORTRAN 90 D, and High Performance FORTRAN. But data parallelism is insufficient for many applications, including adaptive mesh refinement. Without access to both data and task parallelism such applications exhibit several orders of magnitude more message passing and poor performance. In this paper, a C++ array class library is used to implement deferred evaluation and run-time dependence for task parallelism recognition, to obtain task parallelism through a data flow interpretation of data parallel array statements. Performance results show that the analysis and optimizations are both efficient and practical, allowing us to consider more substantial optimizations.<<ETX>>","PeriodicalId":146277,"journal":{"name":"Proceedings of Scalable Parallel Libraries Conference","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of Scalable Parallel Libraries Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPLC.1993.365580","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32

Abstract

This paper explores the use of a run-time system to recognize task parallelism within a C++ array class library. Run-time systems currently support data parallelism in P++, FORTRAN 90 D, and High Performance FORTRAN. But data parallelism is insufficient for many applications, including adaptive mesh refinement. Without access to both data and task parallelism such applications exhibit several orders of magnitude more message passing and poor performance. In this paper, a C++ array class library is used to implement deferred evaluation and run-time dependence for task parallelism recognition, to obtain task parallelism through a data flow interpretation of data parallel array statements. Performance results show that the analysis and optimizations are both efficient and practical, allowing us to consider more substantial optimizations.<>
p++并行数组类库中任务并行性的运行时识别
本文探讨了使用一个运行时系统来识别c++数组类库中的任务并行性。运行时系统目前在p++、FORTRAN 90d和高性能FORTRAN中支持数据并行。但是数据并行性对于许多应用来说是不够的,包括自适应网格细化。如果不能同时访问数据和任务并行性,这样的应用程序会表现出几个数量级的消息传递和较差的性能。本文利用c++数组类库实现任务并行性识别的延迟求值和运行时依赖,通过数据并行数组语句的数据流解释获得任务并行性。性能结果表明,分析和优化既有效又实用,使我们能够考虑更实质性的优化
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:481959085
Book学术官方微信