Simulation-Based Performance Evaluation of an Energy-Aware Heuristic for the Scheduling of HPC Applications in Large-Scale Distributed Systems

Georgios L. Stavrinides, H. Karatza
{"title":"Simulation-Based Performance Evaluation of an Energy-Aware Heuristic for the Scheduling of HPC Applications in Large-Scale Distributed Systems","authors":"Georgios L. Stavrinides, H. Karatza","doi":"10.1145/3053600.3053611","DOIUrl":null,"url":null,"abstract":"As the distributed resources required for the processing of High Performance Computing (HPC) applications are becoming larger in scale and computational capacity, their energy consumption has become a major concern. Therefore, there is a growing focus from both the academia and the industry on the minimization of the carbon footprint of the computational resources, especially through the efficient scheduling of the workload. In this paper, a technique is proposed for the energy-aware scheduling of bag-of-tasks applications with time constraints in a large-scale heterogeneous distributed system. Its performance is evaluated by simulation and compared with a baseline algorithm. The simulation results show that the proposed heuristic not only reduces the energy consumption of the system, but also improves its performance.","PeriodicalId":115833,"journal":{"name":"Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3053600.3053611","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

Abstract

As the distributed resources required for the processing of High Performance Computing (HPC) applications are becoming larger in scale and computational capacity, their energy consumption has become a major concern. Therefore, there is a growing focus from both the academia and the industry on the minimization of the carbon footprint of the computational resources, especially through the efficient scheduling of the workload. In this paper, a technique is proposed for the energy-aware scheduling of bag-of-tasks applications with time constraints in a large-scale heterogeneous distributed system. Its performance is evaluated by simulation and compared with a baseline algorithm. The simulation results show that the proposed heuristic not only reduces the energy consumption of the system, but also improves its performance.
基于仿真的大规模分布式系统中高性能计算应用调度的能量感知启发式性能评估
随着高性能计算(HPC)应用程序处理所需的分布式资源在规模和计算能力上的不断扩大,其能耗已成为人们关注的主要问题。因此,学术界和工业界越来越关注最小化计算资源的碳足迹,特别是通过有效地调度工作负载。本文提出了一种大规模异构分布式系统中具有时间约束的任务袋应用的能量感知调度技术。通过仿真对其性能进行了评价,并与基准算法进行了比较。仿真结果表明,提出的启发式算法不仅降低了系统的能耗,而且提高了系统的性能。
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