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ATLAS Grid Workflow Performance Optimization

The CERN ATLAS experiment grid workflow system manages routinely 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG. At this scale small improvements in t...

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Detalles Bibliográficos
Autores principales: Elmsheuser, Johannes, Di Girolamo, Alessandro
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2625216
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author Elmsheuser, Johannes
Di Girolamo, Alessandro
author_facet Elmsheuser, Johannes
Di Girolamo, Alessandro
author_sort Elmsheuser, Johannes
collection CERN
description The CERN ATLAS experiment grid workflow system manages routinely 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG. At this scale small improvements in the software and computing performance and workflows can lead to significant resource usage gains. ATLAS is reviewing together with CERN IT experts several typical simulation and data processing workloads for potential performance improvements in terms of memory and CPU usage, disk and network I/O. All ATLAS production and analysis grid jobs are instrumented to collect many performance metrics for detailed statistical studies using modern data analytics tools like ElasticSearch and Kibana. This presentation will review and explain the performance gains of several ATLAS simulation and data processing workflows and present analytics studies of the ATLAS grid workflows.
id cern-2625216
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
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spelling cern-26252162019-11-14T09:09:16Zhttp://cds.cern.ch/record/2625216engElmsheuser, JohannesDi Girolamo, AlessandroATLAS Grid Workflow Performance OptimizationParticle Physics - ExperimentThe CERN ATLAS experiment grid workflow system manages routinely 250 to 500 thousand concurrently running production and analysis jobs to process simulation and detector data. In total more than 300 PB of data is distributed over more than 150 sites in the WLCG. At this scale small improvements in the software and computing performance and workflows can lead to significant resource usage gains. ATLAS is reviewing together with CERN IT experts several typical simulation and data processing workloads for potential performance improvements in terms of memory and CPU usage, disk and network I/O. All ATLAS production and analysis grid jobs are instrumented to collect many performance metrics for detailed statistical studies using modern data analytics tools like ElasticSearch and Kibana. This presentation will review and explain the performance gains of several ATLAS simulation and data processing workflows and present analytics studies of the ATLAS grid workflows.ATL-SOFT-SLIDE-2018-390oai:cds.cern.ch:26252162018-06-21
spellingShingle Particle Physics - Experiment
Elmsheuser, Johannes
Di Girolamo, Alessandro
ATLAS Grid Workflow Performance Optimization
title ATLAS Grid Workflow Performance Optimization
title_full ATLAS Grid Workflow Performance Optimization
title_fullStr ATLAS Grid Workflow Performance Optimization
title_full_unstemmed ATLAS Grid Workflow Performance Optimization
title_short ATLAS Grid Workflow Performance Optimization
title_sort atlas grid workflow performance optimization
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2625216
work_keys_str_mv AT elmsheuserjohannes atlasgridworkflowperformanceoptimization
AT digirolamoalessandro atlasgridworkflowperformanceoptimization