J. Dickson, Steven A. Wright, S. Maheswaran, Andy Herdman, Mark C. Miller, S. Jarvis
{"title":"Replicating HPC I/O Workloads with Proxy Applications","authors":"J. Dickson, Steven A. Wright, S. Maheswaran, Andy Herdman, Mark C. Miller, S. Jarvis","doi":"10.1109/PDSW-DISCS.2016.6","DOIUrl":null,"url":null,"abstract":"Large scale simulation performance is dependent on a number of components, however the task of investigation and optimization has long favored computational and communication elements above I/O. Manually extracting the pattern of I/O behavior from a parent application is a useful way of working to address performance issues on a per-application basis, but developing workflows with some degree of automation and flexibility provides a more powerful approach to tackling current and future I/O challenges. In this paper we describe a workload replication workflow that extracts the I/O pattern of an application and recreates its behavior with a flexible proxy application. We demonstrate how simple lightweight characterization can be translated to provide an effective representation of a physics application, and show how a proxy replication can be used as a tool for investigating I/O library paradigms.","PeriodicalId":375550,"journal":{"name":"2016 1st Joint International Workshop on Parallel Data Storage and data Intensive Scalable Computing Systems (PDSW-DISCS)","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 1st Joint International Workshop on Parallel Data Storage and data Intensive Scalable Computing Systems (PDSW-DISCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PDSW-DISCS.2016.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Large scale simulation performance is dependent on a number of components, however the task of investigation and optimization has long favored computational and communication elements above I/O. Manually extracting the pattern of I/O behavior from a parent application is a useful way of working to address performance issues on a per-application basis, but developing workflows with some degree of automation and flexibility provides a more powerful approach to tackling current and future I/O challenges. In this paper we describe a workload replication workflow that extracts the I/O pattern of an application and recreates its behavior with a flexible proxy application. We demonstrate how simple lightweight characterization can be translated to provide an effective representation of a physics application, and show how a proxy replication can be used as a tool for investigating I/O library paradigms.