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Discovering Matter-Antimatter Asymmetries with GPUs
The search for matter-antimatter asymmetries requires highest precision analyses and thus very large datasets and intensive computing. This contribution discusses two complemen- tary approaches where GPU systems have been successfully exploited in this area. Both approaches make use of the CUDA Thru...
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Lenguaje: | eng |
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2015
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Acceso en línea: | https://dx.doi.org/10.3204/DESY-PROC-2014-05/25 http://cds.cern.ch/record/2043875 |
_version_ | 1780947891205963776 |
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author | Reichert, Stefanie |
author_facet | Reichert, Stefanie |
author_sort | Reichert, Stefanie |
collection | CERN |
description | The search for matter-antimatter asymmetries requires highest precision analyses and thus very large datasets and intensive computing. This contribution discusses two complemen- tary approaches where GPU systems have been successfully exploited in this area. Both approaches make use of the CUDA Thrust library which can be used on supported GPUs. The first approach is a generic search for local asymmetries in phase-space distributions of matter and antimatter particle decays. This powerful analysis method has never been used to date due to its high demand in CPU time. The second approach uses the GooFit framework, which is a generic fitting framework that exploits massive parallelisation on GPUs |
id | oai-inspirehep.net-1386631 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2015 |
record_format | invenio |
spelling | oai-inspirehep.net-13866312019-09-30T06:29:59Zdoi:10.3204/DESY-PROC-2014-05/25http://cds.cern.ch/record/2043875engReichert, StefanieDiscovering Matter-Antimatter Asymmetries with GPUsParticle Physics - ExperimentThe search for matter-antimatter asymmetries requires highest precision analyses and thus very large datasets and intensive computing. This contribution discusses two complemen- tary approaches where GPU systems have been successfully exploited in this area. Both approaches make use of the CUDA Thrust library which can be used on supported GPUs. The first approach is a generic search for local asymmetries in phase-space distributions of matter and antimatter particle decays. This powerful analysis method has never been used to date due to its high demand in CPU time. The second approach uses the GooFit framework, which is a generic fitting framework that exploits massive parallelisation on GPUsoai:inspirehep.net:13866312015 |
spellingShingle | Particle Physics - Experiment Reichert, Stefanie Discovering Matter-Antimatter Asymmetries with GPUs |
title | Discovering Matter-Antimatter Asymmetries with GPUs |
title_full | Discovering Matter-Antimatter Asymmetries with GPUs |
title_fullStr | Discovering Matter-Antimatter Asymmetries with GPUs |
title_full_unstemmed | Discovering Matter-Antimatter Asymmetries with GPUs |
title_short | Discovering Matter-Antimatter Asymmetries with GPUs |
title_sort | discovering matter-antimatter asymmetries with gpus |
topic | Particle Physics - Experiment |
url | https://dx.doi.org/10.3204/DESY-PROC-2014-05/25 http://cds.cern.ch/record/2043875 |
work_keys_str_mv | AT reichertstefanie discoveringmatterantimatterasymmetrieswithgpus |