Accelerating detector simulations with Celeritas: profiling and performance optimizations

Amanda L. Lund; Julien Esseiva; Seth R. Johnson; Elliott Biondo; Philippe Canal; Thomas Evans; Hayden Hollenbeck; Soon Yung Jun; Guilherme Lima; Ben Morgan; Stefano C. Tognini

arXiv · 2503.17608

Accelerating detector simulations with Celeritas: profiling and performance optimizations

Amanda L. Lund·Julien Esseiva·Seth R. Johnson·Elliott Biondo·Philippe Canal·Thomas Evans·Hayden Hollenbeck·Soon Yung Jun·Guilherme Lima·Ben Morgan·Stefano C. Tognini

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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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Amanda L. Lund, Julien Esseiva, Seth R. Johnson, Elliott Biondo, Philippe Canal, Thomas Evans, Hayden Hollenbeck, Soon Yung Jun, Guilherme Lima, Ben Morgan, Stefano C. Tognini. 2025-03-22. Accelerating detector simulations with Celeritas: profiling and performance optimizations. https://arxiv.org/abs/2503.17608

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