CnC-Hadoop: a graphical coordination language for distributed multiscale parallelism

Riyaz Haque, David M. Peixotto, Vivek Sarkar
{"title":"CnC-Hadoop: a graphical coordination language for distributed multiscale parallelism","authors":"Riyaz Haque, David M. Peixotto, Vivek Sarkar","doi":"10.1145/2016604.2016626","DOIUrl":null,"url":null,"abstract":"The information-technology platform is being radically transformed with the widespread adoption of the cloud computing model supported by data centers containing large numbers of multicore servers. While cloud computing platforms can potentially enable a rich variety of distributed applications, the need to exploit multiscale parallelism at the inter-node and intra-node level poses significantly new challenges for software. Recent advances in the Google MapReduce and Hadoop frameworks have led to simplified programming models for a restricted class of distributed batch-processing applications. However, these frameworks do not support richer distributed application structures beyond map-reduce, and do not offer any solutions for exploiting shared-memory multicore parallelism at the intra-node level.","PeriodicalId":430420,"journal":{"name":"ACM International Conference on Computing Frontiers","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM International Conference on Computing Frontiers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2016604.2016626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The information-technology platform is being radically transformed with the widespread adoption of the cloud computing model supported by data centers containing large numbers of multicore servers. While cloud computing platforms can potentially enable a rich variety of distributed applications, the need to exploit multiscale parallelism at the inter-node and intra-node level poses significantly new challenges for software. Recent advances in the Google MapReduce and Hadoop frameworks have led to simplified programming models for a restricted class of distributed batch-processing applications. However, these frameworks do not support richer distributed application structures beyond map-reduce, and do not offer any solutions for exploiting shared-memory multicore parallelism at the intra-node level.
CnC-Hadoop:分布式多尺度并行的图形化协调语言
随着包含大量多核服务器的数据中心支持的云计算模型的广泛采用,信息技术平台正在发生根本性的变化。虽然云计算平台可以潜在地实现丰富多样的分布式应用程序,但需要在节点间和节点内级别上利用多尺度并行性,这对软件提出了重大的新挑战。Google MapReduce和Hadoop框架的最新进展已经简化了一类受限的分布式批处理应用程序的编程模型。然而,这些框架不支持除map-reduce之外的更丰富的分布式应用程序结构,并且不提供任何在节点内级别利用共享内存多核并行性的解决方案。
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