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Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework

The processing of data acquired by the CMS detector at LHC is carried out with an object-oriented C++ software framework: CMSSW. With the increasing luminosity delivered by the LHC, the treatment of recorded data requires extraordinary large computing resources, also in terms of CPU usage. A possibl...

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Detalles Bibliográficos
Autores principales: Hauth, T, Innocente, V, Piparo, D
Lenguaje:eng
Publicado: 2012
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/396/5/052065
http://cds.cern.ch/record/1515982
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author Hauth, T
Innocente, V
Piparo, D
author_facet Hauth, T
Innocente, V
Piparo, D
author_sort Hauth, T
collection CERN
description The processing of data acquired by the CMS detector at LHC is carried out with an object-oriented C++ software framework: CMSSW. With the increasing luminosity delivered by the LHC, the treatment of recorded data requires extraordinary large computing resources, also in terms of CPU usage. A possible solution to cope with this task is the exploitation of the features offered by the latest microprocessor architectures. Modern CPUs present several vector units, the capacity of which is growing steadily with the introduction of new processor generations. Moreover, an increasing number of cores per die is offered by the main vendors, even on consumer hardware. Most recent C++ compilers provide facilities to take advantage of such innovations, either by explicit statements in the programs sources or automatically adapting the generated machine instructions to the available hardware, without the need of modifying the existing code base. Programming techniques to implement reconstruction algorithms and optimised data structures are presented, that aim to scalable vectorization and parallelization of the calculations. One of their features is the usage of new language features of the C++11 standard. Portions of the CMSSW framework are illustrated which have been found to be especially profitable for the application of vectorization and multi-threading techniques. Specific utility components have been developed to help vectorization and parallelization. They can easily become part of a larger common library. To conclude, careful measurements are described, which show the execution speedups achieved via vectorised and multi-threaded code in the context of CMSSW.
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institution Organización Europea para la Investigación Nuclear
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publishDate 2012
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spelling cern-15159822022-08-17T13:24:47Zdoi:10.1088/1742-6596/396/5/052065http://cds.cern.ch/record/1515982engHauth, TInnocente, VPiparo, DDevelopment and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software frameworkComputing and ComputersThe processing of data acquired by the CMS detector at LHC is carried out with an object-oriented C++ software framework: CMSSW. With the increasing luminosity delivered by the LHC, the treatment of recorded data requires extraordinary large computing resources, also in terms of CPU usage. A possible solution to cope with this task is the exploitation of the features offered by the latest microprocessor architectures. Modern CPUs present several vector units, the capacity of which is growing steadily with the introduction of new processor generations. Moreover, an increasing number of cores per die is offered by the main vendors, even on consumer hardware. Most recent C++ compilers provide facilities to take advantage of such innovations, either by explicit statements in the programs sources or automatically adapting the generated machine instructions to the available hardware, without the need of modifying the existing code base. Programming techniques to implement reconstruction algorithms and optimised data structures are presented, that aim to scalable vectorization and parallelization of the calculations. One of their features is the usage of new language features of the C++11 standard. Portions of the CMSSW framework are illustrated which have been found to be especially profitable for the application of vectorization and multi-threading techniques. Specific utility components have been developed to help vectorization and parallelization. They can easily become part of a larger common library. To conclude, careful measurements are described, which show the execution speedups achieved via vectorised and multi-threaded code in the context of CMSSW.oai:cds.cern.ch:15159822012
spellingShingle Computing and Computers
Hauth, T
Innocente, V
Piparo, D
Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework
title Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework
title_full Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework
title_fullStr Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework
title_full_unstemmed Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework
title_short Development and evaluation of vectorised and multi-core event reconstruction algorithms within the CMS software framework
title_sort development and evaluation of vectorised and multi-core event reconstruction algorithms within the cms software framework
topic Computing and Computers
url https://dx.doi.org/10.1088/1742-6596/396/5/052065
http://cds.cern.ch/record/1515982
work_keys_str_mv AT hautht developmentandevaluationofvectorisedandmulticoreeventreconstructionalgorithmswithinthecmssoftwareframework
AT innocentev developmentandevaluationofvectorisedandmulticoreeventreconstructionalgorithmswithinthecmssoftwareframework
AT piparod developmentandevaluationofvectorisedandmulticoreeventreconstructionalgorithmswithinthecmssoftwareframework