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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...
Autores principales: | , , , , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
EDP Sciences
2019
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1051/epjconf/201921407021 http://cds.cern.ch/record/2728399 |
_version_ | 1780966434598289408 |
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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 |
record_format | invenio |
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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