迭代应用中增量数据分布的编程框架

Philip Chan, D. Abramson
{"title":"迭代应用中增量数据分布的编程框架","authors":"Philip Chan, D. Abramson","doi":"10.1109/ISPA.2008.105","DOIUrl":null,"url":null,"abstract":"Successful HPC over desktop grids and non-dedicated NOWs is challenging, since good performance is difficult to achieve due to dynamic workloads. On iterative data-parallel applications, this is addressed by dynamic data distribution. However, current approaches migrate an application from one distribution to another in one single phase, which can impact performance. In this paper, we present D3-ARC, a programming framework to support adaptive and incremental data distribution, so that data migration takes place over several successive iterations. D3-ARC consists of a runtime system and an API for specifying the distribution of arrays as well as how data redistribution takes place. We demonstrate how D3-ARC can be used to develop an incremental strategy for data distribution in a Poisson solver, utilising a runtime feedback mechanism to determine how much data to migrate during each iteration.","PeriodicalId":345341,"journal":{"name":"2008 IEEE International Symposium on Parallel and Distributed Processing with Applications","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Programming Framework for Incremental Data Distribution in Iterative Applications\",\"authors\":\"Philip Chan, D. Abramson\",\"doi\":\"10.1109/ISPA.2008.105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Successful HPC over desktop grids and non-dedicated NOWs is challenging, since good performance is difficult to achieve due to dynamic workloads. On iterative data-parallel applications, this is addressed by dynamic data distribution. However, current approaches migrate an application from one distribution to another in one single phase, which can impact performance. In this paper, we present D3-ARC, a programming framework to support adaptive and incremental data distribution, so that data migration takes place over several successive iterations. D3-ARC consists of a runtime system and an API for specifying the distribution of arrays as well as how data redistribution takes place. We demonstrate how D3-ARC can be used to develop an incremental strategy for data distribution in a Poisson solver, utilising a runtime feedback mechanism to determine how much data to migrate during each iteration.\",\"PeriodicalId\":345341,\"journal\":{\"name\":\"2008 IEEE International Symposium on Parallel and Distributed Processing with Applications\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Symposium on Parallel and Distributed Processing with Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2008.105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Symposium on Parallel and Distributed Processing with Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2008.105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在桌面网格和非专用now上成功的HPC是具有挑战性的,因为由于动态工作负载,很难实现良好的性能。在迭代数据并行应用中,这是通过动态数据分布来解决的。然而,当前的方法是在一个阶段内将应用程序从一个发行版迁移到另一个发行版,这可能会影响性能。在本文中,我们提出了D3-ARC,一个支持自适应和增量数据分布的编程框架,这样数据迁移就可以在几个连续的迭代中进行。D3-ARC由一个运行时系统和一个API组成,用于指定数组的分布以及如何进行数据重新分配。我们演示了如何使用D3-ARC来开发泊松求解器中数据分布的增量策略,利用运行时反馈机制来确定每次迭代期间要迁移的数据量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Programming Framework for Incremental Data Distribution in Iterative Applications
Successful HPC over desktop grids and non-dedicated NOWs is challenging, since good performance is difficult to achieve due to dynamic workloads. On iterative data-parallel applications, this is addressed by dynamic data distribution. However, current approaches migrate an application from one distribution to another in one single phase, which can impact performance. In this paper, we present D3-ARC, a programming framework to support adaptive and incremental data distribution, so that data migration takes place over several successive iterations. D3-ARC consists of a runtime system and an API for specifying the distribution of arrays as well as how data redistribution takes place. We demonstrate how D3-ARC can be used to develop an incremental strategy for data distribution in a Poisson solver, utilising a runtime feedback mechanism to determine how much data to migrate during each iteration.
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
期刊最新文献
Image Feature Vector Construction Using Interest Point Based Regions A Fully Dynamic Distributed Algorithm for a B-Coloring of Graphs Fixed Point Decimal Multiplication Using RPS Algorithm Self-Stabilizing Construction of Bounded Size Clusters ScatterClipse: A Model-Driven Tool-Chain for Developing, Testing, and Prototyping Wireless Sensor Networks
×
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