DOE OSTI · 2549343
Accelerating detector simulations with Celeritas: profiling and performance optimizations
Abstract
Celeritas is a GPU-optimized MC particle transport code designed to meet the growing computational demands of next-generation HEP experiments. It provides efficient simulation of EM physics processes in complex geometries with magnetic fields, detector hit scoring, and seamless integration into Geant4-driven applications to offload EM physics to GPUs. Recent efforts have focused on performance optimizations and expanding profiling capabilities. This paper presents some key advancements, including the integration of the Perfetto system profiling tool for detailed performance analysis and the development of track-sorting methods to improve computational efficiency.
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Lund, Amanda L. [Argonne, PHY] (ORCID:0000000283160709), Esseiva, Julien [LBL, Berkeley] (ORCID:0009000211194851), Johnson, Seth R. [Oak Ridge] (ORCID:0000000315048966), Biondo, Elliott [Oak Ridge] (ORCID:0000000290881360), Canal, Philippe [Fermilab] (ORCID:0000000277487887), Evans, Thomas [Oak Ridge] (ORCID:0000000157433788), Hollenbeck, Hayden [Virginia U.], Jun, Soon Yung [Fermilab] (ORCID:0000000333706109), Lima, Guilherme [Fermilab] (ORCID:0000000345850546), Morgan, Ben [Warwick U.] (ORCID:0000000336040883), C. Tognini, Stefano [Oak Ridge] (ORCID:0000000197416608). 2025-03-21. Accelerating detector simulations with Celeritas: profiling and performance optimizations. https://www.osti.gov/biblio/2549343
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