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A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector

<!--HTML-->Starting from the next LHC run, the upgraded LHCb High Level Trigger will process events at the full LHC collision rate (averaging 30 MHz). This challenging goal, tackled using a large and heterogeneous computing farm, can be eased addressing lowest-level, more repetitive tasks at t...

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Autor principal: Bassi, Giovanni
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2766922
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author Bassi, Giovanni
author_facet Bassi, Giovanni
author_sort Bassi, Giovanni
collection CERN
description <!--HTML-->Starting from the next LHC run, the upgraded LHCb High Level Trigger will process events at the full LHC collision rate (averaging 30 MHz). This challenging goal, tackled using a large and heterogeneous computing farm, can be eased addressing lowest-level, more repetitive tasks at the earliest stages of the data acquisition chain. FPGA devices are very well-suited to perform with a high degree of parallelism and efficiency certain computations, that would be significantly demanding if performed on general-purpose architectures. A particularly time-demanding task is the cluster-finding process, due to the 2D pixel geometry of the new LHCb pixel detector. We describe here a custom highly parallel FPGA-based clustering algorithm and its firmware implementation. The algorithm implementation has shown excellent reconstruction quality during qualification tests, while requiring a modest amount of hardware resources. Therefore it can run in the LHCb FPGA readout cards in real time, during data taking at 30 MHz, representing a promising alternative solution to more common CPU-based algorithms.
id cern-2766922
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27669222022-11-02T22:25:52Zhttp://cds.cern.ch/record/2766922engBassi, GiovanniA real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector25th International Conference on Computing in High Energy & Nuclear PhysicsConferences<!--HTML-->Starting from the next LHC run, the upgraded LHCb High Level Trigger will process events at the full LHC collision rate (averaging 30 MHz). This challenging goal, tackled using a large and heterogeneous computing farm, can be eased addressing lowest-level, more repetitive tasks at the earliest stages of the data acquisition chain. FPGA devices are very well-suited to perform with a high degree of parallelism and efficiency certain computations, that would be significantly demanding if performed on general-purpose architectures. A particularly time-demanding task is the cluster-finding process, due to the 2D pixel geometry of the new LHCb pixel detector. We describe here a custom highly parallel FPGA-based clustering algorithm and its firmware implementation. The algorithm implementation has shown excellent reconstruction quality during qualification tests, while requiring a modest amount of hardware resources. Therefore it can run in the LHCb FPGA readout cards in real time, during data taking at 30 MHz, representing a promising alternative solution to more common CPU-based algorithms.oai:cds.cern.ch:27669222021
spellingShingle Conferences
Bassi, Giovanni
A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector
title A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector
title_full A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector
title_fullStr A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector
title_full_unstemmed A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector
title_short A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector
title_sort real-time fpga-based cluster finding algorithm for lhcb silicon pixel detector
topic Conferences
url http://cds.cern.ch/record/2766922
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