An evaluation of GPUs for use in an upgraded ATLAS High Level Trigger Article Swipe
A. Tavares Delgado
,
P. Conde Muíño
,
J. Augusto Soares
,
R. Gonçalo
,
J. T. Baines
,
T. Bołd
,
D. Emeliyanov
,
S. Kama
,
M. Bauce
,
A. Messina
,
M. Negrini
,
A. Sidoti
,
L. Rinaldi
,
S. A. Tupputi
,
Z. D. Greenwood
,
Amber Elliott
,
Supada Laosooksathit
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1109/nssmic.2015.7581786
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1109/nssmic.2015.7581786
ATLAS is a general purpose particle physics experiment located on the LHC collider at CERN. The ATLAS Trigger system consists of two levels, the first level (L1) implemented in hardware and the High Level Trigger (HLT) implemented in software running on a farm of commodity CPU. The HLT reduces the trigger rate from the 100 kHz L1 accept rate to 1 kHz for recording requiring an average per-event processing time of ~250 ms for this task. The HLT selection is based on reconstructing tracks in the Inner Detector and Muon Spectrometer and clusters of energy deposited in the Calorimeter. Performing this reconstruction within the available HLT farm resources presents a significant challenge that will increase significantly after future LHC upgrades resulting in higher detector occupancies. General purpose Graphics Processor Units (GPGPU) are being evaluated for possible future inclusion in an upgraded HLT farm. We report on a demonstrator that has been developed consisting of GPGPU implementations of the Calorimeter clustering and Inner Detector and Muon tracking integrated within the HLT software framework. We give a brief overview of the algorithms implementation and present preliminary measurements comparing the performance of the algorithms implemented on GPU with the CPU versions.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/nssmic.2015.7581786
- OA Status
- green
- Cited By
- 1
- References
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2281858861
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2281858861Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/nssmic.2015.7581786Digital Object Identifier
- Title
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An evaluation of GPUs for use in an upgraded ATLAS High Level TriggerWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2015Year of publication
- Publication date
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2015-10-01Full publication date if available
- Authors
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A. Tavares Delgado, P. Conde Muíño, J. Augusto Soares, R. Gonçalo, J. T. Baines, T. Bołd, D. Emeliyanov, S. Kama, M. Bauce, A. Messina, M. Negrini, A. Sidoti, L. Rinaldi, S. A. Tupputi, Z. D. Greenwood, Amber Elliott, Supada LaosooksathitList of authors in order
- Landing page
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https://doi.org/10.1109/nssmic.2015.7581786Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://cds.cern.ch/record/2104313Direct OA link when available
- Concepts
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Large Hadron Collider, Computer science, Detector, Software, General-purpose computing on graphics processing units, Compact Muon Solenoid, Atlas (anatomy), Event reconstruction, Supercomputer, Computer hardware, Graphics, Operating system, Physics, Particle physics, Biology, Telecommunications, PaleontologyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2016: 1Per-year citation counts (last 5 years)
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8Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.versions. | 197 |
| abstract_inverted_index.Performing | 99 |
| abstract_inverted_index.algorithms | 179, 190 |
| abstract_inverted_index.clustering | 159 |
| abstract_inverted_index.consisting | 152 |
| abstract_inverted_index.experiment | 7 |
| abstract_inverted_index.framework. | 171 |
| abstract_inverted_index.integrated | 166 |
| abstract_inverted_index.processing | 68 |
| abstract_inverted_index.Calorimeter | 158 |
| abstract_inverted_index.implemented | 27, 36, 191 |
| abstract_inverted_index.performance | 187 |
| abstract_inverted_index.preliminary | 183 |
| abstract_inverted_index.significant | 110 |
| abstract_inverted_index.Calorimeter. | 98 |
| abstract_inverted_index.Spectrometer | 90 |
| abstract_inverted_index.demonstrator | 147 |
| abstract_inverted_index.measurements | 184 |
| abstract_inverted_index.occupancies. | 124 |
| abstract_inverted_index.significantly | 115 |
| abstract_inverted_index.implementation | 180 |
| abstract_inverted_index.reconstructing | 82 |
| abstract_inverted_index.reconstruction | 101 |
| abstract_inverted_index.implementations | 155 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 17 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.87251773 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |