Celeritas: GPU-accelerated particle transport for detector simulation in High Energy Physics experiments

TL;DR

Celeritas is a GPU-accelerated Monte Carlo particle transport code designed to meet the high computational demands of future high energy physics experiments, leveraging heterogeneous architectures for full fidelity simulations.

Contribution

The paper introduces Celeritas, a novel GPU-accelerated particle transport code optimized for high fidelity detector simulations in HEP, compatible with exascale computing architectures.

Findings

Designed to leverage heterogeneous architectures including GPUs.

Aims to match Geant4's full fidelity in simulations.

Roadmap for integration with HEP workflows.

Abstract

Within the next decade, experimental High Energy Physics (HEP) will enter a new era of scientific discovery through a set of targeted programs recommended by the Particle Physics Project Prioritization Panel (P5), including the upcoming High Luminosity Large Hadron Collider (LHC) HL-LHC upgrade and the Deep Underground Neutrino Experiment (DUNE). These efforts in the Energy and Intensity Frontiers will require an unprecedented amount of computational capacity on many fronts including Monte Carlo (MC) detector simulation. In order to alleviate this impending computational bottleneck, the Celeritas MC particle transport code is designed to leverage the new generation of heterogeneous computer architectures, including the exascale computing power of U.S. Department of Energy (DOE) Leadership Computing Facilities (LCFs), to model targeted HEP detector problems at the full fidelity of Geant4. This paper presents the planned roadmap for Celeritas, including its proposed code architecture, physics capabilities, and strategies for integrating it with existing and future experimental HEP computing workflows.