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

The Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides more than 2,000 compute nodes, which are critical to ATLAS during data taking. When ATLAS is not recording data, this large com...

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Detalles Bibliográficos
Autores principales: Berghaus, Frank, Brasolin, Franco, Casteels, Kevin, Ebert, Marcus, Leavett-brown, Colin Roy, Lee, Christopher Jon, Love, Peter, Paterson, Michael, Scannicchio, Diana, Seuster, Rolf, Sobie, Randall, Taylor, Ryan P., Di Girolamo, Alessandro, Schovancova, Jaroslava
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2627969
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author Berghaus, Frank
Brasolin, Franco
Casteels, Kevin
Ebert, Marcus
Leavett-brown, Colin Roy
Lee, Christopher Jon
Love, Peter
Paterson, Michael
Scannicchio, Diana
Seuster, Rolf
Sobie, Randall
Taylor, Ryan P.
Di Girolamo, Alessandro
Schovancova, Jaroslava
author_facet Berghaus, Frank
Brasolin, Franco
Casteels, Kevin
Ebert, Marcus
Leavett-brown, Colin Roy
Lee, Christopher Jon
Love, Peter
Paterson, Michael
Scannicchio, Diana
Seuster, Rolf
Sobie, Randall
Taylor, Ryan P.
Di Girolamo, Alessandro
Schovancova, Jaroslava
author_sort Berghaus, Frank
collection CERN
description The Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides more than 2,000 compute nodes, which are critical to ATLAS during data taking. When ATLAS is not recording data, this large compute resource is used to generate and process simulation data for the experiment. 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 resources.
id cern-2627969
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
record_format invenio
spelling cern-26279692019-09-30T06:29:59Zhttp://cds.cern.ch/record/2627969engBerghaus, FrankBrasolin, FrancoCasteels, KevinEbert, MarcusLeavett-brown, Colin RoyLee, Christopher JonLove, PeterPaterson, MichaelScannicchio, DianaSeuster, RolfSobie, RandallTaylor, Ryan P.Di Girolamo, AlessandroSchovancova, JaroslavaSim@P1: Using Cloudscheduler for offline processing on the ATLAS HLT farmParticle Physics - ExperimentThe Simulation at Point1 (Sim@P1) project was built in 2013 to take advantage of the ATLAS Trigger and Data Acquisition High Level Trigger (HLT) farm. The HLT farm provides more than 2,000 compute nodes, which are critical to ATLAS during data taking. When ATLAS is not recording data, this large compute resource is used to generate and process simulation data for the experiment. 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 resources.ATL-SOFT-SLIDE-2018-433oai:cds.cern.ch:26279692018-07-01
spellingShingle Particle Physics - Experiment
Berghaus, Frank
Brasolin, Franco
Casteels, Kevin
Ebert, Marcus
Leavett-brown, Colin Roy
Lee, Christopher Jon
Love, Peter
Paterson, Michael
Scannicchio, Diana
Seuster, Rolf
Sobie, Randall
Taylor, Ryan P.
Di Girolamo, Alessandro
Schovancova, Jaroslava
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 Particle Physics - Experiment
url http://cds.cern.ch/record/2627969
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