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An overview of Celeritas: a novel GPU Monte Carlo detector simulation code

ORAL

Abstract

The next-generation of High Energy Physics (HEP) experiments will rely on a vast increase in detector complexity and data collection, leading to an unprecedented amount of computing storage and processing capacity needs. Contemporary increases in computing capacity are primarily due to the use of heterogeneous architectures that rely on the high performance-per-Watt of GPUs. Celeritas, a new GPU-optimized detector simulation code, seeks to unlock the resources of DOE's Leadership Computing Facilities (LCFs) and the next generation of computing grid hardware for HEP experiments. Early results show a 40× speedup factor for standalone EM simulations on LCF computers when using GPUs. This talk will provide an overview of Celeritas, focusing on its physics capabilities and integration with the CPU-based detector simulation code Geant4. Current Celeritas' electromagnetic (EM) physics models for electrons, positrons, and photons will be verified against Geant4, with an additional verification for coupled offloading, where Geant4 processes hadronic and decay physics but sends EM particles to Celeritas, with an estimated speedup of 2–3× compared to a Geant4-only run. The presentation will also preview future plans for integration with HEP experiments, of which EM offloading is the first step.

Presenters

  • Stefano C. Tognini

    Oak Ridge National Laboratory

Authors

  • Stefano C. Tognini

    Oak Ridge National Laboratory

  • Seth R Johnson

    Oak Ridge National Laboratory

  • Soon Yung Jun

    Fermi National Accelerator Laboratory

  • Amanda L Lund

    Argonne National Laboratory

  • Thomas M Evans

    Oak Ridge National Laboratory

  • Philippe Canal

    Fermi National Accelerator Laboratory

  • Paul K Romano

    Argonne National Laboratory

  • Guilherme Lima

    Fermi National Accelerator Laboratory