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Evolution of the energy efficiency of LHCb’s real-time processing

The upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4 TB/s in real time. Because LHCb’s physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this bandw...

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Autores principales: Aaij, Roel, Cámpora Pérez, Daniel Hugo, Colombo, Tommaso, Fitzpatrick, Conor, Gligorov, Vladimir Vava, Hennequin, Arthur, Neufeld, Niko, Nolte, Niklas, Schwemmer, Rainer, Vom Bruch, Dorothea
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/202125104009
http://cds.cern.ch/record/2773126
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author Aaij, Roel
Cámpora Pérez, Daniel Hugo
Colombo, Tommaso
Fitzpatrick, Conor
Gligorov, Vladimir Vava
Hennequin, Arthur
Neufeld, Niko
Nolte, Niklas
Schwemmer, Rainer
Vom Bruch, Dorothea
author_facet Aaij, Roel
Cámpora Pérez, Daniel Hugo
Colombo, Tommaso
Fitzpatrick, Conor
Gligorov, Vladimir Vava
Hennequin, Arthur
Neufeld, Niko
Nolte, Niklas
Schwemmer, Rainer
Vom Bruch, Dorothea
author_sort Aaij, Roel
collection CERN
description The upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4 TB/s in real time. Because LHCb’s physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this bandwidth challenge is equivalent to that of the ATLAS and CMS HL-LHC software read-out, but deliverable five years earlier. Over the past six years, the LHCb collaboration has undertaken a bottom-up rewrite of its software infrastructure, pattern recognition, and selection algorithms to make them better able to efficiently exploit modern highly parallel computing architectures. We review the impact of this reoptimization on the energy efficiency of the realtime processing software and hardware which will be used for the upgrade of the LHCb detector. We also review the impact of the decision to adopt a hybrid computing architecture consisting of GPUs and CPUs for the real-time part of LHCb’s future data processing. We discuss the implications of these results on how LHCb’s real-time power requirements may evolve in the future, particularly in the context of a planned second upgrade of the detector.
id cern-2773126
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27731262023-10-12T05:28:42Zdoi:10.1051/epjconf/202125104009http://cds.cern.ch/record/2773126engAaij, RoelCámpora Pérez, Daniel HugoColombo, TommasoFitzpatrick, ConorGligorov, Vladimir VavaHennequin, ArthurNeufeld, NikoNolte, NiklasSchwemmer, RainerVom Bruch, DorotheaEvolution of the energy efficiency of LHCb’s real-time processingParticle Physics - ExperimentDetectors and Experimental TechniquesThe upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4 TB/s in real time. Because LHCb’s physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this bandwidth challenge is equivalent to that of the ATLAS and CMS HL-LHC software read-out, but deliverable five years earlier. Over the past six years, the LHCb collaboration has undertaken a bottom-up rewrite of its software infrastructure, pattern recognition, and selection algorithms to make them better able to efficiently exploit modern highly parallel computing architectures. We review the impact of this reoptimization on the energy efficiency of the realtime processing software and hardware which will be used for the upgrade of the LHCb detector. We also review the impact of the decision to adopt a hybrid computing architecture consisting of GPUs and CPUs for the real-time part of LHCb’s future data processing. We discuss the implications of these results on how LHCb’s real-time power requirements may evolve in the future, particularly in the context of a planned second upgrade of the detector.The upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4~TB/s in real time. Because LHCb's physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this bandwidth challenge is equivalent to that of the ATLAS and CMS HL-LHC software read-out, but deliverable five years earlier. Over the past six years, the LHCb collaboration has undertaken a bottom-up rewrite of its software infrastructure, pattern recognition, and selection algorithms to make them better able to efficiently exploit modern highly parallel computing architectures. We review the impact of this reoptimization on the energy efficiency of the real-time processing software and hardware which will be used for the upgrade of the LHCb detector. We also review the impact of the decision to adopt a hybrid computing architecture consisting of GPUs and CPUs for the real-time part of LHCb's future data processing. We discuss the implications of these results on how LHCb's real-time power requirements may evolve in the future, particularly in the context of a planned second upgrade of the detector.arXiv:2106.07701oai:cds.cern.ch:27731262021
spellingShingle Particle Physics - Experiment
Detectors and Experimental Techniques
Aaij, Roel
Cámpora Pérez, Daniel Hugo
Colombo, Tommaso
Fitzpatrick, Conor
Gligorov, Vladimir Vava
Hennequin, Arthur
Neufeld, Niko
Nolte, Niklas
Schwemmer, Rainer
Vom Bruch, Dorothea
Evolution of the energy efficiency of LHCb’s real-time processing
title Evolution of the energy efficiency of LHCb’s real-time processing
title_full Evolution of the energy efficiency of LHCb’s real-time processing
title_fullStr Evolution of the energy efficiency of LHCb’s real-time processing
title_full_unstemmed Evolution of the energy efficiency of LHCb’s real-time processing
title_short Evolution of the energy efficiency of LHCb’s real-time processing
title_sort evolution of the energy efficiency of lhcb’s real-time processing
topic Particle Physics - Experiment
Detectors and Experimental Techniques
url https://dx.doi.org/10.1051/epjconf/202125104009
http://cds.cern.ch/record/2773126
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