Converting a High Performance Application to an Elastic Cloud Application

D. Rajan, Anthony Canino, J. Izaguirre, D. Thain
{"title":"Converting a High Performance Application to an Elastic Cloud Application","authors":"D. Rajan, Anthony Canino, J. Izaguirre, D. Thain","doi":"10.1109/CloudCom.2011.58","DOIUrl":null,"url":null,"abstract":"Over the past decade, high performance applications have embraced parallel programming and computing models. While parallel computing offers advantages such as good utilization of dedicated hardware resources, it also has several drawbacks such as poor fault-tolerance, scalability, and ability to harness available resources during run-time. The advent of cloud computing presents a viable and promising alternative to parallel computing because of its advantages in offering a distributed computing model. In this work, we establish directives that serve as guidelines for the design and implementation or identification of a suitable cloud computing framework to build or convert a high performance application to run in the cloud. We show that following these directives leads to an elastic implementation that has better scalability, run-time resource adaptability, fault tolerance, and portability across cloud computing platforms, while requiring minimal effort and intervention from the user. We illustrate this by converting an MPI implementation of replica exchange, a parallel tempering molecular dynamics application, to an elastic cloud application using the Work Queue framework that adheres to these directive. We observe better scalability and resource adaptability of this elastic application on multiple platforms, including a homogeneous cluster environment (SGE) and heterogeneous cloud computing environments such as Microsoft Azure and Amazon EC2.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"59","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudCom.2011.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 59

Abstract

Over the past decade, high performance applications have embraced parallel programming and computing models. While parallel computing offers advantages such as good utilization of dedicated hardware resources, it also has several drawbacks such as poor fault-tolerance, scalability, and ability to harness available resources during run-time. The advent of cloud computing presents a viable and promising alternative to parallel computing because of its advantages in offering a distributed computing model. In this work, we establish directives that serve as guidelines for the design and implementation or identification of a suitable cloud computing framework to build or convert a high performance application to run in the cloud. We show that following these directives leads to an elastic implementation that has better scalability, run-time resource adaptability, fault tolerance, and portability across cloud computing platforms, while requiring minimal effort and intervention from the user. We illustrate this by converting an MPI implementation of replica exchange, a parallel tempering molecular dynamics application, to an elastic cloud application using the Work Queue framework that adheres to these directive. We observe better scalability and resource adaptability of this elastic application on multiple platforms, including a homogeneous cluster environment (SGE) and heterogeneous cloud computing environments such as Microsoft Azure and Amazon EC2.
将高性能应用转换为弹性云应用
在过去的十年中,高性能应用程序已经采用了并行编程和计算模型。虽然并行计算提供了一些优势,比如可以很好地利用专用硬件资源,但它也有一些缺点,比如容错性差、可伸缩性差,以及在运行时利用可用资源的能力差。云计算的出现为并行计算提供了一个可行且有前途的替代方案,因为它在提供分布式计算模型方面具有优势。在这项工作中,我们建立了一些指令,作为设计和实现或识别合适的云计算框架的指导方针,以构建或转换高性能应用程序以在云中运行。我们表明,遵循这些指令可以获得弹性实现,该实现具有更好的可伸缩性、运行时资源适应性、容错性和跨云计算平台的可移植性,同时只需要用户最少的努力和干预。我们通过将副本交换的MPI实现(一个并行调优分子动力学应用程序)转换为使用遵循这些指令的工作队列框架的弹性云应用程序来说明这一点。我们观察到这种弹性应用程序在多个平台上具有更好的可伸缩性和资源适应性,包括同构集群环境(SGE)和异构云计算环境(如Microsoft Azure和Amazon EC2)。
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:604180095
Book学术官方微信