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The Retina Algorithm
<!--HTML-->Charge particle reconstruction is one of the most demanding computational tasks found in HEP, and it becomes increasingly important to perform it in real time. We envision that HEP would greatly benefit from achieving a long-term goal of making track reconstruction happen transparen...
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Lenguaje: | eng |
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2015
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Acceso en línea: | http://cds.cern.ch/record/2093524 |
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author | RISTORI, Luciano Frances PUNZI, Giovanni |
author_facet | RISTORI, Luciano Frances PUNZI, Giovanni |
author_sort | RISTORI, Luciano Frances |
collection | CERN |
description | <!--HTML-->Charge particle reconstruction is one of the most demanding computational tasks found in HEP, and it becomes increasingly important to perform it in real time. We envision that HEP would greatly benefit from achieving a long-term goal of making track reconstruction happen transparently as part of the detector readout ("detector-embedded tracking"). We describe here a track-reconstruction approach based on a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature ('RETINA algorithm'). It turns out that high-quality tracking in large HEP detectors is possible with very small latencies, when this algorithm is implemented in specialized processors, based on current state-of-the-art, high-speed/high-bandwidth digital devices. |
id | cern-2093524 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2015 |
record_format | invenio |
spelling | cern-20935242022-11-02T22:33:48Zhttp://cds.cern.ch/record/2093524engRISTORI, Luciano FrancesPUNZI, GiovanniThe Retina AlgorithmData Science @ LHC 2015 WorkshopLPCC Workshops<!--HTML-->Charge particle reconstruction is one of the most demanding computational tasks found in HEP, and it becomes increasingly important to perform it in real time. We envision that HEP would greatly benefit from achieving a long-term goal of making track reconstruction happen transparently as part of the detector readout ("detector-embedded tracking"). We describe here a track-reconstruction approach based on a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature ('RETINA algorithm'). It turns out that high-quality tracking in large HEP detectors is possible with very small latencies, when this algorithm is implemented in specialized processors, based on current state-of-the-art, high-speed/high-bandwidth digital devices.oai:cds.cern.ch:20935242015 |
spellingShingle | LPCC Workshops RISTORI, Luciano Frances PUNZI, Giovanni The Retina Algorithm |
title | The Retina Algorithm |
title_full | The Retina Algorithm |
title_fullStr | The Retina Algorithm |
title_full_unstemmed | The Retina Algorithm |
title_short | The Retina Algorithm |
title_sort | retina algorithm |
topic | LPCC Workshops |
url | http://cds.cern.ch/record/2093524 |
work_keys_str_mv | AT ristorilucianofrances theretinaalgorithm AT punzigiovanni theretinaalgorithm AT ristorilucianofrances datasciencelhc2015workshop AT punzigiovanni datasciencelhc2015workshop AT ristorilucianofrances retinaalgorithm AT punzigiovanni retinaalgorithm |