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Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator

<!--HTML-->Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern hardware architectures, such as those deployed at...

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Detalles Bibliográficos
Autor principal: Valassi, Andrea
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:https://dx.doi.org/10.17181/CERN.ESFS.PYDP
http://cds.cern.ch/record/2767144
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author Valassi, Andrea
author_facet Valassi, Andrea
author_sort Valassi, Andrea
collection CERN
description <!--HTML-->Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern hardware architectures, such as those deployed at HPC centers, is essential in view of the upcoming HL-LHC physics programme. In this contribution, we describe an ongoing activity to reengineer the Madgraph5_aMC@NLO physics event generator, primarily to port it and allow its efficient execution on GPUs, but also to modernize it and optimize its performance on traditional CPUs. In our presentation at the conference, we will describe the motivation, engineering process and software architecture design of our developments, as well as some of the challenges and future directions for this project. We also plan to present the status and results of our developments at the time of the presentation, including detailed software performance metrics.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
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spelling cern-27671442022-11-02T22:25:39Zdoi:10.17181/CERN.ESFS.PYDPhttp://cds.cern.ch/record/2767144engValassi, AndreaDesign and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator25th International Conference on Computing in High Energy & Nuclear PhysicsConferences<!--HTML-->Physics event generators are essential components of the data analysis software chain of high energy physics experiments, and important consumers of their CPU resources. Improving the software performance of these packages on modern hardware architectures, such as those deployed at HPC centers, is essential in view of the upcoming HL-LHC physics programme. In this contribution, we describe an ongoing activity to reengineer the Madgraph5_aMC@NLO physics event generator, primarily to port it and allow its efficient execution on GPUs, but also to modernize it and optimize its performance on traditional CPUs. In our presentation at the conference, we will describe the motivation, engineering process and software architecture design of our developments, as well as some of the challenges and future directions for this project. We also plan to present the status and results of our developments at the time of the presentation, including detailed software performance metrics.oai:cds.cern.ch:27671442021
spellingShingle Conferences
Valassi, Andrea
Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator
title Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator
title_full Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator
title_fullStr Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator
title_full_unstemmed Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator
title_short Design and engineering of a simplified GPU workflow execution for the Madgraph5_aMC@NLO event generator
title_sort design and engineering of a simplified gpu workflow execution for the madgraph5_amc@nlo event generator
topic Conferences
url https://dx.doi.org/10.17181/CERN.ESFS.PYDP
http://cds.cern.ch/record/2767144
work_keys_str_mv AT valassiandrea designandengineeringofasimplifiedgpuworkflowexecutionforthemadgraph5amcnloeventgenerator
AT valassiandrea 25thinternationalconferenceoncomputinginhighenergynuclearphysics