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Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm

The Simulation at Point1 (Sim@P1) project was established in 2013 to take advantage of the Trigger and Data Acquisition High Level Trigger (HLT) farm of the ATLAS experiment at the LHC. The HLT farm is a significant compute resource, which is critical to ATLAS during data taking. This large compute...

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Autores principales: Berghaus, Frank, Brasolin, Franco, Casteels, Kevin, Driemel, Colson, Ebert, Marcus, Leavatt-Brown, Colin, Lee, Chris, Love, Peter, Paterson, Michael, Scannicchio, Diana, Seuster, Rolf, Sobie, Randall, Weiss-Gibbons, Tahya
Lenguaje:eng
Publicado: EDP Sciences 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/201921407021
http://cds.cern.ch/record/2728399
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author Berghaus, Frank
Brasolin, Franco
Casteels, Kevin
Driemel, Colson
Ebert, Marcus
Leavatt-Brown, Colin
Lee, Chris
Love, Peter
Paterson, Michael
Scannicchio, Diana
Seuster, Rolf
Sobie, Randall
Weiss-Gibbons, Tahya
author_facet Berghaus, Frank
Brasolin, Franco
Casteels, Kevin
Driemel, Colson
Ebert, Marcus
Leavatt-Brown, Colin
Lee, Chris
Love, Peter
Paterson, Michael
Scannicchio, Diana
Seuster, Rolf
Sobie, Randall
Weiss-Gibbons, Tahya
author_sort Berghaus, Frank
collection CERN
description The Simulation at Point1 (Sim@P1) project was established in 2013 to take advantage of the Trigger and Data Acquisition High Level Trigger (HLT) farm of the ATLAS experiment at the LHC. The HLT farm is a significant compute resource, which is critical to ATLAS during data taking. This large compute resource is used to generate and process simulation data for the experiment when ATLAS is not recording data. The Sim@P1 system uses virtual machines, deployed by OpenStack, in order to isolate the resources from the ATLAS technical and control network. During the upcoming long shutdown in 2019 (LS2), the HLT farm including the Sim@P1 infrastructure will be upgraded. A previous paper on the project emphasized the need for “simple, reliable, and efficient tools” to quickly switch between data acquisition operation and offline processing. In this contribution we assess various options for updating and simplifying the provisional tools. Cloudscheduler is a tool for provisioning cloud resources for batch computing that has been managing cloud resources in HEP offline computing since 2012. We present the argument for choosing Cloudscheduler, and describe technical details regarding optimal utilization of the Sim@P1 re-sources.
id oai-inspirehep.net-1761585
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
publisher EDP Sciences
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spelling oai-inspirehep.net-17615852020-08-24T14:53:32Zdoi:10.1051/epjconf/201921407021http://cds.cern.ch/record/2728399engBerghaus, FrankBrasolin, FrancoCasteels, KevinDriemel, ColsonEbert, MarcusLeavatt-Brown, ColinLee, ChrisLove, PeterPaterson, MichaelScannicchio, DianaSeuster, RolfSobie, RandallWeiss-Gibbons, TahyaSim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farmComputing and ComputersThe Simulation at Point1 (Sim@P1) project was established in 2013 to take advantage of the Trigger and Data Acquisition High Level Trigger (HLT) farm of the ATLAS experiment at the LHC. The HLT farm is a significant compute resource, which is critical to ATLAS during data taking. This large compute resource is used to generate and process simulation data for the experiment when ATLAS is not recording data. The Sim@P1 system uses virtual machines, deployed by OpenStack, in order to isolate the resources from the ATLAS technical and control network. During the upcoming long shutdown in 2019 (LS2), the HLT farm including the Sim@P1 infrastructure will be upgraded. A previous paper on the project emphasized the need for “simple, reliable, and efficient tools” to quickly switch between data acquisition operation and offline processing. In this contribution we assess various options for updating and simplifying the provisional tools. Cloudscheduler is a tool for provisioning cloud resources for batch computing that has been managing cloud resources in HEP offline computing since 2012. We present the argument for choosing Cloudscheduler, and describe technical details regarding optimal utilization of the Sim@P1 re-sources.EDP Sciencesoai:inspirehep.net:17615852019
spellingShingle Computing and Computers
Berghaus, Frank
Brasolin, Franco
Casteels, Kevin
Driemel, Colson
Ebert, Marcus
Leavatt-Brown, Colin
Lee, Chris
Love, Peter
Paterson, Michael
Scannicchio, Diana
Seuster, Rolf
Sobie, Randall
Weiss-Gibbons, Tahya
Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm
title Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm
title_full Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm
title_fullStr Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm
title_full_unstemmed Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm
title_short Sim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farm
title_sort sim@p1: using cloudscheduler for offline processing on the atlas hlt farm
topic Computing and Computers
url https://dx.doi.org/10.1051/epjconf/201921407021
http://cds.cern.ch/record/2728399
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