Tirthak Patel, Adam Wagenhäuser, C. Eibel, Timo Hönig, T. Zeiser, Devesh Tiwari
{"title":"What does Power Consumption Behavior of HPC Jobs Reveal? : Demystifying, Quantifying, and Predicting Power Consumption Characteristics","authors":"Tirthak Patel, Adam Wagenhäuser, C. Eibel, Timo Hönig, T. Zeiser, Devesh Tiwari","doi":"10.1109/IPDPS47924.2020.00087","DOIUrl":null,"url":null,"abstract":"As we approach exascale computing, large-scale HPC systems are becoming increasingly power-constrained, requiring them to run HPC workloads in an energy-efficient manner. The first step toward achieving this goal is to better understand, analyze, and quantify the power consumption characteristics of HPC jobs. However, there is a lack of understanding of the power consumption characteristics of HPC jobs which run on production HPC systems. Such characterization is required to guide the design of the next generation of power-aware resource management. To the best of our knowledge, we are the first study to open-source the data and analysis of power-consumption characteristics of HPC jobs and users from two medium-scale production HPC clusters.","PeriodicalId":6805,"journal":{"name":"2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"14 1","pages":"799-809"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS47924.2020.00087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
As we approach exascale computing, large-scale HPC systems are becoming increasingly power-constrained, requiring them to run HPC workloads in an energy-efficient manner. The first step toward achieving this goal is to better understand, analyze, and quantify the power consumption characteristics of HPC jobs. However, there is a lack of understanding of the power consumption characteristics of HPC jobs which run on production HPC systems. Such characterization is required to guide the design of the next generation of power-aware resource management. To the best of our knowledge, we are the first study to open-source the data and analysis of power-consumption characteristics of HPC jobs and users from two medium-scale production HPC clusters.