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CLUE a clustering algorithm for current and future experiments

CLUE (CLUstering of Energy) is a fast parallel clustering algorithm for High Granularity Calorimeters in High Energy Physics. In these types of detectors, the standard clustering algorithms using combinatorics are expected to fail due to large number of digitized energy deposits (hits) in the recons...

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Detalles Bibliográficos
Autor principal: Brondolin, Erica
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/2438/1/012074
http://cds.cern.ch/record/2802590
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author Brondolin, Erica
author_facet Brondolin, Erica
author_sort Brondolin, Erica
collection CERN
description CLUE (CLUstering of Energy) is a fast parallel clustering algorithm for High Granularity Calorimeters in High Energy Physics. In these types of detectors, the standard clustering algorithms using combinatorics are expected to fail due to large number of digitized energy deposits (hits) in the reconstruction stage bringing to a consequent memory/timing explosion. This innovative algorithm uses a grid spatial index for fast querying of neighbors and its timing scales linearly with the number of hits within the range considered. Initially CLUE was developed in a standalone repository that allows performance benchmarking with respect to its CPU and GPU implementations, demonstrating the power of algorithmic parallelization in the coming era of heterogeneous computing. CLUE has been successfully used in simulation and beam tests of the High Granularity Calorimeter to be installed for the upgrade of the CMS detector in Phase-2 of the HL-LHC. Recently CLUE was also imported in the key4hep framework and first results will be shown for detectors proposed in future collider projects.
id cern-2802590
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2022
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spelling cern-28025902023-08-23T07:56:31Zdoi:10.1088/1742-6596/2438/1/012074http://cds.cern.ch/record/2802590engBrondolin, EricaCLUE a clustering algorithm for current and future experimentsDetectors and Experimental TechniquesCLUE (CLUstering of Energy) is a fast parallel clustering algorithm for High Granularity Calorimeters in High Energy Physics. In these types of detectors, the standard clustering algorithms using combinatorics are expected to fail due to large number of digitized energy deposits (hits) in the reconstruction stage bringing to a consequent memory/timing explosion. This innovative algorithm uses a grid spatial index for fast querying of neighbors and its timing scales linearly with the number of hits within the range considered. Initially CLUE was developed in a standalone repository that allows performance benchmarking with respect to its CPU and GPU implementations, demonstrating the power of algorithmic parallelization in the coming era of heterogeneous computing. CLUE has been successfully used in simulation and beam tests of the High Granularity Calorimeter to be installed for the upgrade of the CMS detector in Phase-2 of the HL-LHC. Recently CLUE was also imported in the key4hep framework and first results will be shown for detectors proposed in future collider projects.CMS-CR-2022-027oai:cds.cern.ch:28025902022-02-01
spellingShingle Detectors and Experimental Techniques
Brondolin, Erica
CLUE a clustering algorithm for current and future experiments
title CLUE a clustering algorithm for current and future experiments
title_full CLUE a clustering algorithm for current and future experiments
title_fullStr CLUE a clustering algorithm for current and future experiments
title_full_unstemmed CLUE a clustering algorithm for current and future experiments
title_short CLUE a clustering algorithm for current and future experiments
title_sort clue a clustering algorithm for current and future experiments
topic Detectors and Experimental Techniques
url https://dx.doi.org/10.1088/1742-6596/2438/1/012074
http://cds.cern.ch/record/2802590
work_keys_str_mv AT brondolinerica clueaclusteringalgorithmforcurrentandfutureexperiments