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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...
Autores principales: | , , , , , , |
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Lenguaje: | eng |
Publicado: |
2017
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/898/5/052030 http://cds.cern.ch/record/2297170 |
_version_ | 1780956901280841728 |
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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 |
record_format | invenio |
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 |
work_keys_str_mv | AT perezcaleroyzquierdoa cmsreadinessformulticoreworkloadscheduling AT balcasj cmsreadinessformulticoreworkloadscheduling AT hernandezj cmsreadinessformulticoreworkloadscheduling AT aftabkhanf cmsreadinessformulticoreworkloadscheduling AT lettsj cmsreadinessformulticoreworkloadscheduling AT masond cmsreadinessformulticoreworkloadscheduling AT verguilovv cmsreadinessformulticoreworkloadscheduling |