Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events Article Swipe
G. B. Cerati
,
P. Elmer
,
Brian Gravelle
,
M. J. Kortelainen
,
V. Krutelyov
,
Steven Lantz
,
Matthieu Lefèbvre
,
Mario Masciovecchio
,
K. Mcdermott
,
Boyana Norris
,
Allison Reinsvold Hall
,
Daniel Riley
,
M. Tadel
,
P. Wittich
,
Frank Würthwein
,
Avi Yagil
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1811.04141
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1811.04141
The High-Luminosity Large Hadron Collider at CERN will be characterized by greater pileup of events and higher occupancy, making the track reconstruction even more computationally demanding. Existing algorithms at the LHC are based on Kalman filter techniques with proven excellent physics performance under a variety of conditions. Starting in 2014, we have been developing Kalman-filter-based methods for track finding and fitting adapted for many-core SIMD processors that are becoming dominant in high-performance systems. This paper summarizes the latest extensions to our software that allow it to run on the realistic CMS-2017 tracker geometry using CMSSW-generated events, including pileup. The reconstructed tracks can be validated against either the CMSSW simulation that generated the hits, or the CMSSW reconstruction of the tracks. In general, the code's computational performance has continued to improve while the above capabilities were being added. We demonstrate that the present Kalman filter implementation is able to reconstruct events with comparable physics performance to CMSSW, while providing generally better computational performance. Further plans for advancing the software are discussed.
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Metadata
- Type
- article
- Language
- en
- OA Status
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- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4289299399Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1811.04141Digital Object Identifier
- Title
-
Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and EventsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-11-09Full publication date if available
- Authors
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G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov, Steven Lantz, Matthieu Lefèbvre, Mario Masciovecchio, K. Mcdermott, Boyana Norris, Allison Reinsvold Hall, Daniel Riley, M. Tadel, P. Wittich, Frank Würthwein, Avi YagilList of authors in order
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/1525458Direct OA link when available
- Concepts
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Kalman filter, Tracking (education), Detector, Geometry, Computer science, Computer vision, Computer graphics (images), Artificial intelligence, Physics, Mathematics, Optics, Psychology, PedagogyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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