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Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker

The High-Luminosity upgrade of the Large Hadron Collider (LHC) will see the accelerator reach an instantaneous luminosity of 7 × 10(34) cm(−2) s(−1) with an average pileup of 200 proton-proton collisions. These conditions will pose an unprecedented challenge to the online and offline reconstruction...

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Autores principales: Bocci, A., Innocente, V., Kortelainen, M., Pantaleo, F., Rovere, M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931873/
https://www.ncbi.nlm.nih.gov/pubmed/33693424
http://dx.doi.org/10.3389/fdata.2020.601728
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author Bocci, A.
Innocente, V.
Kortelainen, M.
Pantaleo, F.
Rovere, M.
author_facet Bocci, A.
Innocente, V.
Kortelainen, M.
Pantaleo, F.
Rovere, M.
author_sort Bocci, A.
collection PubMed
description The High-Luminosity upgrade of the Large Hadron Collider (LHC) will see the accelerator reach an instantaneous luminosity of 7 × 10(34) cm(−2) s(−1) with an average pileup of 200 proton-proton collisions. These conditions will pose an unprecedented challenge to the online and offline reconstruction software developed by the experiments. The computational complexity will exceed by far the expected increase in processing power for conventional CPUs, demanding an alternative approach. Industry and High-Performance Computing (HPC) centers are successfully using heterogeneous computing platforms to achieve higher throughput and better energy efficiency by matching each job to the most appropriate architecture. In this paper we will describe the results of a heterogeneous implementation of pixel tracks and vertices reconstruction chain on Graphics Processing Units (GPUs). The framework has been designed and developed to be integrated in the CMS reconstruction software, CMSSW. The speed up achieved by leveraging GPUs allows for more complex algorithms to be executed, obtaining better physics output and a higher throughput.
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spelling pubmed-79318732021-03-09 Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker Bocci, A. Innocente, V. Kortelainen, M. Pantaleo, F. Rovere, M. Front Big Data Big Data The High-Luminosity upgrade of the Large Hadron Collider (LHC) will see the accelerator reach an instantaneous luminosity of 7 × 10(34) cm(−2) s(−1) with an average pileup of 200 proton-proton collisions. These conditions will pose an unprecedented challenge to the online and offline reconstruction software developed by the experiments. The computational complexity will exceed by far the expected increase in processing power for conventional CPUs, demanding an alternative approach. Industry and High-Performance Computing (HPC) centers are successfully using heterogeneous computing platforms to achieve higher throughput and better energy efficiency by matching each job to the most appropriate architecture. In this paper we will describe the results of a heterogeneous implementation of pixel tracks and vertices reconstruction chain on Graphics Processing Units (GPUs). The framework has been designed and developed to be integrated in the CMS reconstruction software, CMSSW. The speed up achieved by leveraging GPUs allows for more complex algorithms to be executed, obtaining better physics output and a higher throughput. Frontiers Media S.A. 2020-12-21 /pmc/articles/PMC7931873/ /pubmed/33693424 http://dx.doi.org/10.3389/fdata.2020.601728 Text en Copyright © 2020 Bocci, Innocente, Kortelainen, Pantaleo and Rovere http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Bocci, A.
Innocente, V.
Kortelainen, M.
Pantaleo, F.
Rovere, M.
Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker
title Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker
title_full Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker
title_fullStr Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker
title_full_unstemmed Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker
title_short Heterogeneous Reconstruction of Tracks and Primary Vertices With the CMS Pixel Tracker
title_sort heterogeneous reconstruction of tracks and primary vertices with the cms pixel tracker
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931873/
https://www.ncbi.nlm.nih.gov/pubmed/33693424
http://dx.doi.org/10.3389/fdata.2020.601728
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