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CMS readiness for multi-core workload scheduling

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining s...

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Detalles Bibliográficos
Autores principales: Perez-Calero Yzquierdo, A, Balcas, J, Hernandez, J, Aftab Khan, F, Letts, J, Mason, D, Verguilov, V
Lenguaje:eng
Publicado: 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/898/5/052030
http://cds.cern.ch/record/2297170
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author Perez-Calero Yzquierdo, A
Balcas, J
Hernandez, J
Aftab Khan, F
Letts, J
Mason, D
Verguilov, V
author_facet Perez-Calero Yzquierdo, A
Balcas, J
Hernandez, J
Aftab Khan, F
Letts, J
Mason, D
Verguilov, V
author_sort Perez-Calero Yzquierdo, A
collection CERN
description In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.
id oai-inspirehep.net-1638487
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
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spelling oai-inspirehep.net-16384872021-02-09T10:06:55Zdoi:10.1088/1742-6596/898/5/052030http://cds.cern.ch/record/2297170engPerez-Calero Yzquierdo, ABalcas, JHernandez, JAftab Khan, FLetts, JMason, DVerguilov, VCMS readiness for multi-core workload schedulingComputing and ComputersIn the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.oai:inspirehep.net:16384872017
spellingShingle Computing and Computers
Perez-Calero Yzquierdo, A
Balcas, J
Hernandez, J
Aftab Khan, F
Letts, J
Mason, D
Verguilov, V
CMS readiness for multi-core workload scheduling
title CMS readiness for multi-core workload scheduling
title_full CMS readiness for multi-core workload scheduling
title_fullStr CMS readiness for multi-core workload scheduling
title_full_unstemmed CMS readiness for multi-core workload scheduling
title_short CMS readiness for multi-core workload scheduling
title_sort cms readiness for multi-core workload scheduling
topic Computing and Computers
url https://dx.doi.org/10.1088/1742-6596/898/5/052030
http://cds.cern.ch/record/2297170
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