GPGPU for track finding in High Energy Physics Article Swipe
L. Rinaldi
,
Mauro Belgiovine
,
R. Di Sipio
,
A. Gabrielli
,
M. Negrini
,
F. Semeria
,
A. Sidoti
,
S. A. Tupputi
,
M. Villa
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1507.03074
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1507.03074
The LHC experiments are designed to detect large amount of physics events produced with a very high rate. Considering the future upgrades, the data acquisition rate will become even higher and new computing paradigms must be adopted for fast data-processing: General Purpose Graphics Processing Units (GPGPU) is a novel approach based on massive parallel computing. The intense computation power provided by Graphics Processing Units (GPU) is expected to reduce the computation time and to speed-up the low-latency applications used for fast decision taking. In particular, this approach could be hence used for high-level triggering in very complex environments, like the typical inner tracking systems of the multi-purpose experiments at LHC, where a large number of charged particle tracks will be produced with the luminosity upgrade. In this article we discuss a track pattern recognition algorithm based on the Hough Transform, where a parallel approach is expected to reduce dramatically the execution time.
Related Topics
Concepts
General-purpose computing on graphics processing units
Graphics
Large Hadron Collider
Upgrade
Computer science
Computation
Track (disk drive)
Computational science
Tracking (education)
Computer graphics (images)
Parallel computing
Algorithm
Physics
Particle physics
Operating system
Psychology
Pedagogy
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1507.03074
- https://arxiv.org/pdf/1507.03074
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394639016
All OpenAlex metadata
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https://openalex.org/W4394639016Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1507.03074Digital Object Identifier
- Title
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GPGPU for track finding in High Energy PhysicsWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-07-11Full publication date if available
- Authors
-
L. Rinaldi, Mauro Belgiovine, R. Di Sipio, A. Gabrielli, M. Negrini, F. Semeria, A. Sidoti, S. A. Tupputi, M. VillaList of authors in order
- Landing page
-
https://arxiv.org/abs/1507.03074Publisher landing page
- PDF URL
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https://arxiv.org/pdf/1507.03074Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/1507.03074Direct OA link when available
- Concepts
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General-purpose computing on graphics processing units, Graphics, Large Hadron Collider, Upgrade, Computer science, Computation, Track (disk drive), Computational science, Tracking (education), Computer graphics (images), Parallel computing, Algorithm, Physics, Particle physics, Operating system, Psychology, PedagogyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2022: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.time. | 151 |
| abstract_inverted_index.track | 131 |
| abstract_inverted_index.where | 110, 140 |
| abstract_inverted_index.amount | 8 |
| abstract_inverted_index.become | 27 |
| abstract_inverted_index.detect | 6 |
| abstract_inverted_index.events | 11 |
| abstract_inverted_index.future | 20 |
| abstract_inverted_index.higher | 29 |
| abstract_inverted_index.number | 113 |
| abstract_inverted_index.reduce | 68, 147 |
| abstract_inverted_index.tracks | 117 |
| abstract_inverted_index.(GPGPU) | 45 |
| abstract_inverted_index.General | 40 |
| abstract_inverted_index.Purpose | 41 |
| abstract_inverted_index.adopted | 36 |
| abstract_inverted_index.article | 127 |
| abstract_inverted_index.charged | 115 |
| abstract_inverted_index.complex | 96 |
| abstract_inverted_index.discuss | 129 |
| abstract_inverted_index.intense | 56 |
| abstract_inverted_index.massive | 52 |
| abstract_inverted_index.pattern | 132 |
| abstract_inverted_index.physics | 10 |
| abstract_inverted_index.systems | 103 |
| abstract_inverted_index.taking. | 82 |
| abstract_inverted_index.typical | 100 |
| abstract_inverted_index.Graphics | 42, 61 |
| abstract_inverted_index.approach | 49, 86, 143 |
| abstract_inverted_index.decision | 81 |
| abstract_inverted_index.designed | 4 |
| abstract_inverted_index.expected | 66, 145 |
| abstract_inverted_index.parallel | 53, 142 |
| abstract_inverted_index.particle | 116 |
| abstract_inverted_index.produced | 12, 120 |
| abstract_inverted_index.provided | 59 |
| abstract_inverted_index.speed-up | 74 |
| abstract_inverted_index.tracking | 102 |
| abstract_inverted_index.upgrade. | 124 |
| abstract_inverted_index.algorithm | 134 |
| abstract_inverted_index.computing | 32 |
| abstract_inverted_index.execution | 150 |
| abstract_inverted_index.paradigms | 33 |
| abstract_inverted_index.upgrades, | 21 |
| abstract_inverted_index.Processing | 43, 62 |
| abstract_inverted_index.Transform, | 139 |
| abstract_inverted_index.computing. | 54 |
| abstract_inverted_index.high-level | 92 |
| abstract_inverted_index.luminosity | 123 |
| abstract_inverted_index.triggering | 93 |
| abstract_inverted_index.Considering | 18 |
| abstract_inverted_index.acquisition | 24 |
| abstract_inverted_index.computation | 57, 70 |
| abstract_inverted_index.experiments | 2, 107 |
| abstract_inverted_index.low-latency | 76 |
| abstract_inverted_index.particular, | 84 |
| abstract_inverted_index.recognition | 133 |
| abstract_inverted_index.applications | 77 |
| abstract_inverted_index.dramatically | 148 |
| abstract_inverted_index.environments, | 97 |
| abstract_inverted_index.multi-purpose | 106 |
| abstract_inverted_index.data-processing: | 39 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.7900000214576721 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile |