{"title":"不同工作负载下的高性能计算软件跟踪策略","authors":"Heechang Na, Zhi-Qiang You, Troy Baer, Shameema Oottikkal, Trey Dockendorf, Scott Brozell","doi":"10.1109/HUSTProtools51951.2020.00008","DOIUrl":null,"url":null,"abstract":"This paper discusses and reviews various tools that Ohio Supercomputer Center (OSC) uses for tracking High-Performance Computing (HPC) software usage. Tracking software usage is a key element to support a diverse user community. OSC maintains three data pools: batch job database, data from user executions, and license server logs. We utilize various tools and databases to collect, store and analyze software usage data. These includes pbsacct, Spark, XALT, Lmod, Splunk, License log, Ganglia, and Prometheus/Grafana. We discuss the coverage and gaps for each pool and present some use cases.","PeriodicalId":38836,"journal":{"name":"Meta: Avaliacao","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"HPC Software Tracking Strategies for a Diverse Workload\",\"authors\":\"Heechang Na, Zhi-Qiang You, Troy Baer, Shameema Oottikkal, Trey Dockendorf, Scott Brozell\",\"doi\":\"10.1109/HUSTProtools51951.2020.00008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses and reviews various tools that Ohio Supercomputer Center (OSC) uses for tracking High-Performance Computing (HPC) software usage. Tracking software usage is a key element to support a diverse user community. OSC maintains three data pools: batch job database, data from user executions, and license server logs. We utilize various tools and databases to collect, store and analyze software usage data. These includes pbsacct, Spark, XALT, Lmod, Splunk, License log, Ganglia, and Prometheus/Grafana. We discuss the coverage and gaps for each pool and present some use cases.\",\"PeriodicalId\":38836,\"journal\":{\"name\":\"Meta: Avaliacao\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Meta: Avaliacao\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HUSTProtools51951.2020.00008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Meta: Avaliacao","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HUSTProtools51951.2020.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
HPC Software Tracking Strategies for a Diverse Workload
This paper discusses and reviews various tools that Ohio Supercomputer Center (OSC) uses for tracking High-Performance Computing (HPC) software usage. Tracking software usage is a key element to support a diverse user community. OSC maintains three data pools: batch job database, data from user executions, and license server logs. We utilize various tools and databases to collect, store and analyze software usage data. These includes pbsacct, Spark, XALT, Lmod, Splunk, License log, Ganglia, and Prometheus/Grafana. We discuss the coverage and gaps for each pool and present some use cases.
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