Author:
Elmsheuser Johannes,Di Girolamo Alessandro,Filipcic Andrej,Limosani Antonio,Schulz Markus,Smith David,Sciaba Andrea,Valassi Andrea
Abstract
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 370 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 tosignificant 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 ATLASproduction 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.
Reference11 articles.
1. Overview of ATLAS PanDA Workload Management
2. Experiences with the new ATLAS Distributed Data Management System
3. Worldwide LHC Computing Grid project, URL
http://cern.ch/lcg
[accessed 2018-09-06]
4. ROOT,
Version 6.14/04 available from
https://root.cern.ch/downloading-root [accessed 2018-09-10]
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