{"title":"AppEKG:生产环境中HPC应用的简单统一视图","authors":"M. Al-Tahat, Strahinja Trecakov, J. Cook","doi":"10.1109/PMBS56514.2022.00017","DOIUrl":null,"url":null,"abstract":"While many good development-oriented tools exist for analyzing and improving the performance of HPC applications, capability for capturing and analyzing the dynamic behavior of application in real production runs is lacking. Many heavily-used applications do keep some internal metrics of their performance, but there is no unified way of using these. In this paper we present the initial idea of AppEKG, both a concept of and a prototype tool for providing a unified, understandable view of HPC application behavior in production. Our prototype AppEKG framework can achieve less than 1% overhead, thus usable in production, and still provide dynamic data collection that captures time-varying runtime behavior.","PeriodicalId":321991,"journal":{"name":"2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AppEKG: A Simple Unifying View of HPC Applications in Production\",\"authors\":\"M. Al-Tahat, Strahinja Trecakov, J. Cook\",\"doi\":\"10.1109/PMBS56514.2022.00017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While many good development-oriented tools exist for analyzing and improving the performance of HPC applications, capability for capturing and analyzing the dynamic behavior of application in real production runs is lacking. Many heavily-used applications do keep some internal metrics of their performance, but there is no unified way of using these. In this paper we present the initial idea of AppEKG, both a concept of and a prototype tool for providing a unified, understandable view of HPC application behavior in production. Our prototype AppEKG framework can achieve less than 1% overhead, thus usable in production, and still provide dynamic data collection that captures time-varying runtime behavior.\",\"PeriodicalId\":321991,\"journal\":{\"name\":\"2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PMBS56514.2022.00017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PMBS56514.2022.00017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AppEKG: A Simple Unifying View of HPC Applications in Production
While many good development-oriented tools exist for analyzing and improving the performance of HPC applications, capability for capturing and analyzing the dynamic behavior of application in real production runs is lacking. Many heavily-used applications do keep some internal metrics of their performance, but there is no unified way of using these. In this paper we present the initial idea of AppEKG, both a concept of and a prototype tool for providing a unified, understandable view of HPC application behavior in production. Our prototype AppEKG framework can achieve less than 1% overhead, thus usable in production, and still provide dynamic data collection that captures time-varying runtime behavior.