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MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes

<!--HTML-->In this proceedings we present MadFlow, a new framework for the automation of Monte Carlo (MC) simulation on graphics processing units (GPU) for particle physics processes. In order to automate MC simulation for a generic number of processes, we design a program which provides to th...

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Detalles Bibliográficos
Autor principal: Cruz Martínez, Juan M.
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2767266
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author Cruz Martínez, Juan M.
author_facet Cruz Martínez, Juan M.
author_sort Cruz Martínez, Juan M.
collection CERN
description <!--HTML-->In this proceedings we present MadFlow, a new framework for the automation of Monte Carlo (MC) simulation on graphics processing units (GPU) for particle physics processes. In order to automate MC simulation for a generic number of processes, we design a program which provides to the user the possibility to simulate custom processes through the MG5_aMC@NLO framework. The pipeline includes a first stage where the analytic expressions for matrix elements and phase space are generated and exported in a GPU-like format. The simulation is then performed using the VegasFlow and PDFFlow libraries which deploy automatically the full simulation on systems with different hardware acceleration capabilities, such as multi-threading CPU, single-GPU and multi-GPU setups. We show some preliminary results for leading-order simulations on different hardware configurations.
id cern-2767266
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27672662022-11-02T22:25:37Zhttp://cds.cern.ch/record/2767266engCruz Martínez, Juan M.MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes25th International Conference on Computing in High Energy & Nuclear PhysicsConferences<!--HTML-->In this proceedings we present MadFlow, a new framework for the automation of Monte Carlo (MC) simulation on graphics processing units (GPU) for particle physics processes. In order to automate MC simulation for a generic number of processes, we design a program which provides to the user the possibility to simulate custom processes through the MG5_aMC@NLO framework. The pipeline includes a first stage where the analytic expressions for matrix elements and phase space are generated and exported in a GPU-like format. The simulation is then performed using the VegasFlow and PDFFlow libraries which deploy automatically the full simulation on systems with different hardware acceleration capabilities, such as multi-threading CPU, single-GPU and multi-GPU setups. We show some preliminary results for leading-order simulations on different hardware configurations.oai:cds.cern.ch:27672662021
spellingShingle Conferences
Cruz Martínez, Juan M.
MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
title MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
title_full MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
title_fullStr MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
title_full_unstemmed MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
title_short MadFlow: towards the automation of Monte Carlo simulation on GPU for particle physics processes
title_sort madflow: towards the automation of monte carlo simulation on gpu for particle physics processes
topic Conferences
url http://cds.cern.ch/record/2767266
work_keys_str_mv AT cruzmartinezjuanm madflowtowardstheautomationofmontecarlosimulationongpuforparticlephysicsprocesses
AT cruzmartinezjuanm 25thinternationalconferenceoncomputinginhighenergynuclearphysics