Using ATLAS@Home to exploit extra CPU from busy grid sites

November 29, 2018 ยท Declared Dead ยท ๐Ÿ› Computing and Software for Big Science

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Authors Wenjing Wu, David Cameron, Qing Di arXiv ID 1811.12578 Category physics.comp-ph Cross-listed cs.DC, hep-ex Citations 3 Venue Computing and Software for Big Science Last Checked 1 month ago
Abstract
Grid computing typically provides most of the data processing resources for large High Energy Physics experiments. However typical grid sites are not fully utilized by regular workloads. In order to increase the CPU utilization of these grid sites, the ATLAS@Home volunteer computing framework can be used as a backfilling mechanism. Results show an extra 15% to 42% of CPU cycles can be exploited by backfilling grid sites running regular workloads while the overall CPU utilization can remain over 90%. Backfilling has no impact on the failure rate of the grid jobs, and the impact on the CPU efficiency of grid jobs varies from 1% to 11% depending on the configuration of the site. In addition the throughput of backfill jobs in terms of CPU time per simulated event is the same as for resources dedicated to ATLAS@Home. This approach is sufficiently generic that it can easily be extended to other clusters.
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