| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 11005 | |
| Number of page(s) | 9 | |
| Section | Heterogeneous Computing and Accelerators | |
| DOI | https://doi.org/10.1051/epjconf/202429511005 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429511005
Celeritas: Accelerating Geant4 with GPUs*
1 Oak Ridge National Laboratory, Oak Ridge, TN, USA
2 Fermi National Accelerator Laboratory, Batavia, IL, USA
3 Argonne National Laboratory, Lemont, IL, USA
4 Lawrence Berkeley National Laboratory, Berkeley, CA, USA
** e-mail: johnsonsr@ornl.gov
Published online: 6 May 2024
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.
This manuscript has been authored in part by UT–Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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