Triggering events with GPUs at ATLAS Article Swipe
S. Kama
,
J. Augusto Soares
,
J. T. Baines
,
M. Bauce
,
T. Bołd
,
P. Conde Muíño
,
D. Emeliyanov
,
R. Gonçalo
,
A. Messina
,
M. Negrini
,
L. Rinaldi
,
A. Sidoti
,
A. Tavares Delgado
,
S. A. Tupputi
,
L. Vaz Gil Lopes
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/664/9/092014
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/664/9/092014
The growing complexity of events produced in LHC collisions demands more and more computing power both for the online selection and for the offline reconstruction of events. In recent years, the explosive performance growth of massively parallel processors like Graphics Processing Units~(GPU) both in computing power and in low energy consumption, make GPU extremely attractive for using them in a complex high energy experiment like ATLAS. Together with the optimization of reconstruction algorithms this new massively parallel paradigm is exploited. For this purpose a small scale prototype of the full ATLAS High Level Trigger involving GPU has been implemented. We discuss the integration procedure of this prototype, the achieved performance and the prospects for the future
Related Topics
Concepts
Massively parallel
Computer science
Exploit
Atlas (anatomy)
Large Hadron Collider
Graphics
Power consumption
Supercomputer
Graphics processing unit
Computational science
Parallel computing
Computer graphics (images)
Power (physics)
Particle physics
Physics
Paleontology
Computer security
Quantum mechanics
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/664/9/092014
- https://iopscience.iop.org/article/10.1088/1742-6596/664/9/092014/pdf
- OA Status
- diamond
- Cited By
- 1
- References
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2207663189
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2207663189Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1742-6596/664/9/092014Digital Object Identifier
- Title
-
Triggering events with GPUs at ATLASWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-12-23Full publication date if available
- Authors
-
S. Kama, J. Augusto Soares, J. T. Baines, M. Bauce, T. Bołd, P. Conde Muíño, D. Emeliyanov, R. Gonçalo, A. Messina, M. Negrini, L. Rinaldi, A. Sidoti, A. Tavares Delgado, S. A. Tupputi, L. Vaz Gil LopesList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/664/9/092014Publisher landing page
- PDF URL
-
https://iopscience.iop.org/article/10.1088/1742-6596/664/9/092014/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1742-6596/664/9/092014/pdfDirect OA link when available
- Concepts
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Massively parallel, Computer science, Exploit, Atlas (anatomy), Large Hadron Collider, Graphics, Power consumption, Supercomputer, Graphics processing unit, Computational science, Parallel computing, Computer graphics (images), Power (physics), Particle physics, Physics, Paleontology, Computer security, Quantum mechanics, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2015: 1Per-year citation counts (last 5 years)
- References (count)
-
1Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| corresponding_author_ids | https://openalex.org/A5109895814 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I178169726 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8999999761581421 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.87029231 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |