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CITATION.cff
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# Pleace cite the following article when referencing Celeritas in a publication:
#
# (Plain text, Chicago author-date 17th ed):
# Johnson, Seth R., Amanda Lund, Philippe Canal, Stefano C. Tognini, Julien
# Esseiva, Soon Yung Jun, Guilherme Lima, et al. 2024. “Celeritas:
# Accelerating Geant4 with GPUs.” EPJ Web of Conferences 295:11005.
# https://doi.org/10.1051/epjconf/202429511005.
#
# (BibLaTeX):
# @article{celer-chep-2024,
# title = {Celeritas: {{Accelerating Geant4}} with {{GPUs}}},
# author = {Johnson, Seth R. and Lund, Amanda and Canal, Philippe and Tognini, Stefano C. and Esseiva, Julien and Jun, Soon Yung and Lima, Guilherme and Biondo, Elliott and Evans, Thomas and Demarteau, Marcel and Romano, Paul},
# date = {2024},
# journaltitle = {EPJ Web of Conferences},
# volume = {295},
# pages = {11005},
# doi = {10.1051/epjconf/202429511005}
# }
#
# Note: This information is also present in the README.md and needs to
# kept in sync.
#
# (CFF):
cff-version: 1.2.0
type: software
message: "Please cite the following article when referencing Celeritas in a publication."
title: "Celeritas"
type: software
license:
- Apache-2.0
- MIT
authors:
- family-names: Johnson
given-names: Seth R.
orcid: "https://orcid.org/0000-0003-1504-8966"
- family-names: Lund
given-names: Amanda
orcid: "https://orcid.org/0000-0002-8316-0709"
- family-names: Jun
given-names: Soon Yung
orcid: "https://orcid.org/0000-0003-3370-6109"
- family-names: Tognini
given-names: Stefano
orcid: "https://orcid.org/0000-0001-9741-6608"
- family-names: Lima
given-names: Guilherme
orcid: "https://orcid.org/0000-0003-4585-0546"
- family-names: Canal
given-names: Philippe
orcid: "https://orcid.org/0000-0002-7748-7887"
- family-names: Morgan
given-names: Ben
- family-names: Evans
given-names: Tom
orcid: "https://orcid.org/0000-0001-5743-3788"
- family-names: Esseiva
given-names: Julien
date-released: 2022
url: https://doi.org/10.11578/dc.20221011.1
identifiers:
- type: doi
value: 10.11578/dc.20221011.1
keywords:
- monte carlo
- particle transport
- high energy physics
- detector simulation
- computational physics
- hep
- cuda
- hip
preferred-citation:
authors:
- family-names: Johnson
given-names: Seth R.
orcid: "https://orcid.org/0000-0003-1504-8966"
- family-names: Lund
given-names: Amanda
orcid: "https://orcid.org/0000-0002-8316-0709"
- family-names: Canal
given-names: Philippe
orcid: "https://orcid.org/0000-0002-7748-7887"
- family-names: Tognini
given-names: Stefano C.
orcid: "https://orcid.org/0000-0001-9741-6608"
- family-names: Esseiva
given-names: Julien
- family-names: Jun
given-names: Soon Yung
orcid: "https://orcid.org/0000-0003-3370-6109"
- family-names: Lima
given-names: Guilherme
orcid: "https://orcid.org/0000-0003-4585-0546"
- family-names: Biondo
given-names: Elliott
- family-names: Evans
given-names: Thomas
orcid: "https://orcid.org/0000-0001-5743-3788"
- family-names: Demarteau
given-names: Marcel
- family-names: Romano
given-names: Paul
orcid: "https://orcid.org/0000-0002-1147-045X"
title: "Celeritas: Accelerating Geant4 with GPUs"
type: article
journal: "EPJ Web of Conferences"
volume: 295
number: 11005
issue-title: "26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)"
date-published: 2024
identifiers:
- type: doi
value: 10.1051/epjconf/202429511005
abstract: >-
Celeritas is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Luminosity 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.