Celeritas: Accelerating Geant4 with GPUs Article Swipe
S. R. Johnson
,
Julien Esseiva
,
Elliott Biondo
,
Philippe Canal
,
M. Demarteau
,
Thomas Evans
,
S. Y. Jun
,
J. G. R. Lima
,
Amanda Lund
,
Paul Romano
,
S. C. Tognini
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1051/epjconf/202429511005
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1051/epjconf/202429511005
Celeritas [1] is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Lumi- nosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6 and 32 faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1051/epjconf/202429511005
- https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_11005.pdf
- OA Status
- diamond
- Cited By
- 5
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396680284
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4396680284Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1051/epjconf/202429511005Digital Object Identifier
- Title
-
Celeritas: Accelerating Geant4 with GPUsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-01Full publication date if available
- Authors
-
S. R. Johnson, Julien Esseiva, Elliott Biondo, Philippe Canal, M. Demarteau, Thomas Evans, S. Y. Jun, J. G. R. Lima, Amanda Lund, Paul Romano, S. C. TogniniList of authors in order
- Landing page
-
https://doi.org/10.1051/epjconf/202429511005Publisher landing page
- PDF URL
-
https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_11005.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.epj-conferences.org/articles/epjconf/pdf/2024/05/epjconf_chep2024_11005.pdfDirect OA link when available
- Concepts
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Large Hadron Collider, Speedup, Monte Carlo method, Supercomputer, Detector, Computational science, Physics, Dynamical simulation, Parallel computing, Computer science, Particle physics, Mathematics, Optics, Statistics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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5Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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9Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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