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A parallelised ROOT for future HEP data processing

In the coming years, HEP data processing will need to exploit parallelism on present and future hardware resources to sustain the bandwidth requirements. As one of the cornerstones of the HEP software ecosystem, ROOT embraced an ambitious parallelisation plan which delivered compelling results. In t...

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Detalles Bibliográficos
Autores principales: Piparo, Danilo, Canal, Philippe, Amadio, Guilherme, Guiraud, Enrico, Naumann, Axel, Valls, Xavier, Tejedor, Enric
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/201921405033
http://cds.cern.ch/record/2699850
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author Piparo, Danilo
Canal, Philippe
Amadio, Guilherme
Guiraud, Enrico
Naumann, Axel
Valls, Xavier
Tejedor, Enric
author_facet Piparo, Danilo
Canal, Philippe
Amadio, Guilherme
Guiraud, Enrico
Naumann, Axel
Valls, Xavier
Tejedor, Enric
author_sort Piparo, Danilo
collection CERN
description In the coming years, HEP data processing will need to exploit parallelism on present and future hardware resources to sustain the bandwidth requirements. As one of the cornerstones of the HEP software ecosystem, ROOT embraced an ambitious parallelisation plan which delivered compelling results. In this contribution the strategy is characterised as well as its evolution in the medium term. The units of the ROOT framework are discussed where task and data parallelism have been introduced, with runtime and scaling measurements. We will give an overview of concurrent operations in ROOT, for instance in the areas of I/O (reading and writing of data), fitting/minimization, and data analysis. This paper introduces the programming model and use cases for explicit and implicit parallelism, where the former is explicit in user code and the latter is implicitly managed by ROOT internally.
id oai-inspirehep.net-1761253
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
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spelling oai-inspirehep.net-17612532022-08-10T12:22:34Zdoi:10.1051/epjconf/201921405033http://cds.cern.ch/record/2699850engPiparo, DaniloCanal, PhilippeAmadio, GuilhermeGuiraud, EnricoNaumann, AxelValls, XavierTejedor, EnricA parallelised ROOT for future HEP data processingComputing and ComputersIn the coming years, HEP data processing will need to exploit parallelism on present and future hardware resources to sustain the bandwidth requirements. As one of the cornerstones of the HEP software ecosystem, ROOT embraced an ambitious parallelisation plan which delivered compelling results. In this contribution the strategy is characterised as well as its evolution in the medium term. The units of the ROOT framework are discussed where task and data parallelism have been introduced, with runtime and scaling measurements. We will give an overview of concurrent operations in ROOT, for instance in the areas of I/O (reading and writing of data), fitting/minimization, and data analysis. This paper introduces the programming model and use cases for explicit and implicit parallelism, where the former is explicit in user code and the latter is implicitly managed by ROOT internally.FERMILAB-CONF-19-551-SCDoai:inspirehep.net:17612532019
spellingShingle Computing and Computers
Piparo, Danilo
Canal, Philippe
Amadio, Guilherme
Guiraud, Enrico
Naumann, Axel
Valls, Xavier
Tejedor, Enric
A parallelised ROOT for future HEP data processing
title A parallelised ROOT for future HEP data processing
title_full A parallelised ROOT for future HEP data processing
title_fullStr A parallelised ROOT for future HEP data processing
title_full_unstemmed A parallelised ROOT for future HEP data processing
title_short A parallelised ROOT for future HEP data processing
title_sort parallelised root for future hep data processing
topic Computing and Computers
url https://dx.doi.org/10.1051/epjconf/201921405033
http://cds.cern.ch/record/2699850
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