Cargando…

Storage Element performance optimization for CMS analysis jobs

Tier-2 computing sites in the Worldwide Large Hadron Collider Computing Grid (WLCG) host CPU-resources (Compute Element, CE) and storage resources (Storage Element, SE). The vast amount of data that needs to processed from the Large Hadron Collider (LHC) experiments requires good and efficient use o...

Descripción completa

Detalles Bibliográficos
Autores principales: Behrmann, Gert, Dahlblom, Jonas, Guldmyr, Johan, Happonen, Kalle, Linden, Tomas
Lenguaje:eng
Publicado: 2012
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/396/4/042037
http://cds.cern.ch/record/1457866
_version_ 1780925140937211904
author Behrmann, Gert
Dahlblom, Jonas
Guldmyr, Johan
Happonen, Kalle
Linden, Tomas
author_facet Behrmann, Gert
Dahlblom, Jonas
Guldmyr, Johan
Happonen, Kalle
Linden, Tomas
author_sort Behrmann, Gert
collection CERN
description Tier-2 computing sites in the Worldwide Large Hadron Collider Computing Grid (WLCG) host CPU-resources (Compute Element, CE) and storage resources (Storage Element, SE). The vast amount of data that needs to processed from the Large Hadron Collider (LHC) experiments requires good and efficient use of the available resources. Having a good CPU efficiency for the end users analysis jobs requires that the performance of the storage system is able to scale with I/O requests from hundreds or even thousands of simultaneous jobs. In this presentation we report on the work on improving the SE performance at the Helsinki Institute of Physics (HIP) Tier-2 used for the Compact Muon Experiment (CMS) at the LHC. Statistics from CMS grid jobs are collected and stored in the CMS Dashboard for further analysis, which allows for easy performance monitoring by the sites and by the CMS collaboration. As part of the monitoring framework CMS uses the JobRobot which sends every four hours 100 analysis jobs to each site. CMS also uses the HammerCloud (HC) tool for site monitoring and stress testing and HC has replaced the JobRobot. The performance of the analysis workflow submitted with JobRobot or HC can be used to track the performance due to site configuration changes, since the analysis workflow is kept the same for all sites and for months in time. The CPU efficiency of the JobRobot jobs at HIP was increased approximately by 50 % to more than 90 %, by tuning the SE and by improvements in the CMSSW and dCache software. The performance of the CMS analysis jobs improved significantly too. Similar work has been done on other CMS Tier-sites, since on average the CPU efficiency for CMSSW jobs has increased during 2011. Better monitoring of the SE allows faster detection of problems, so that the performance level can be kept high. The next storage upgrade at HIP will consist of SAS disk enclosures which can be stress tested on demand with HC workflows, to make sure that the I/O-performance is good.
id cern-1457866
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2012
record_format invenio
spelling cern-14578662019-09-30T06:29:59Zdoi:10.1088/1742-6596/396/4/042037http://cds.cern.ch/record/1457866engBehrmann, GertDahlblom, JonasGuldmyr, JohanHapponen, KalleLinden, TomasStorage Element performance optimization for CMS analysis jobsDetectors and Experimental TechniquesTier-2 computing sites in the Worldwide Large Hadron Collider Computing Grid (WLCG) host CPU-resources (Compute Element, CE) and storage resources (Storage Element, SE). The vast amount of data that needs to processed from the Large Hadron Collider (LHC) experiments requires good and efficient use of the available resources. Having a good CPU efficiency for the end users analysis jobs requires that the performance of the storage system is able to scale with I/O requests from hundreds or even thousands of simultaneous jobs. In this presentation we report on the work on improving the SE performance at the Helsinki Institute of Physics (HIP) Tier-2 used for the Compact Muon Experiment (CMS) at the LHC. Statistics from CMS grid jobs are collected and stored in the CMS Dashboard for further analysis, which allows for easy performance monitoring by the sites and by the CMS collaboration. As part of the monitoring framework CMS uses the JobRobot which sends every four hours 100 analysis jobs to each site. CMS also uses the HammerCloud (HC) tool for site monitoring and stress testing and HC has replaced the JobRobot. The performance of the analysis workflow submitted with JobRobot or HC can be used to track the performance due to site configuration changes, since the analysis workflow is kept the same for all sites and for months in time. The CPU efficiency of the JobRobot jobs at HIP was increased approximately by 50 % to more than 90 %, by tuning the SE and by improvements in the CMSSW and dCache software. The performance of the CMS analysis jobs improved significantly too. Similar work has been done on other CMS Tier-sites, since on average the CPU efficiency for CMSSW jobs has increased during 2011. Better monitoring of the SE allows faster detection of problems, so that the performance level can be kept high. The next storage upgrade at HIP will consist of SAS disk enclosures which can be stress tested on demand with HC workflows, to make sure that the I/O-performance is good.CMS-CR-2012-097oai:cds.cern.ch:14578662012-05-15
spellingShingle Detectors and Experimental Techniques
Behrmann, Gert
Dahlblom, Jonas
Guldmyr, Johan
Happonen, Kalle
Linden, Tomas
Storage Element performance optimization for CMS analysis jobs
title Storage Element performance optimization for CMS analysis jobs
title_full Storage Element performance optimization for CMS analysis jobs
title_fullStr Storage Element performance optimization for CMS analysis jobs
title_full_unstemmed Storage Element performance optimization for CMS analysis jobs
title_short Storage Element performance optimization for CMS analysis jobs
title_sort storage element performance optimization for cms analysis jobs
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1088/1742-6596/396/4/042037
http://cds.cern.ch/record/1457866
work_keys_str_mv AT behrmanngert storageelementperformanceoptimizationforcmsanalysisjobs
AT dahlblomjonas storageelementperformanceoptimizationforcmsanalysisjobs
AT guldmyrjohan storageelementperformanceoptimizationforcmsanalysisjobs
AT happonenkalle storageelementperformanceoptimizationforcmsanalysisjobs
AT lindentomas storageelementperformanceoptimizationforcmsanalysisjobs