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Development and Evaluation of Vectorised and Multi-Core Event Reconstruction Algorithms within the CMS Software Framework

<!--HTML-->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...

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Autor principal: Hauth, Thomas
Lenguaje:eng
Publicado: 2012
Materias:
Acceso en línea:http://cds.cern.ch/record/1460883
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author Hauth, Thomas
author_facet Hauth, Thomas
author_sort Hauth, Thomas
collection CERN
description <!--HTML-->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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publishDate 2012
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spelling cern-14608832022-11-02T22:23:31Zhttp://cds.cern.ch/record/1460883engHauth, ThomasDevelopment and Evaluation of Vectorised and Multi-Core Event Reconstruction Algorithms within the CMS Software FrameworkComputing in High Energy and Nuclear Physics (CHEP) 2012Conferences<!--HTML-->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.oai:cds.cern.ch:14608832012
spellingShingle Conferences
Hauth, Thomas
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 Conferences
url http://cds.cern.ch/record/1460883
work_keys_str_mv AT hauththomas developmentandevaluationofvectorisedandmulticoreeventreconstructionalgorithmswithinthecmssoftwareframework
AT hauththomas computinginhighenergyandnuclearphysicschep2012