Comparison and efficiency of GPU accelerated optical light propagation in CORSIKA 8

TL;DR

This paper evaluates GPU acceleration techniques for optical light propagation in CORSIKA 8, focusing on performance, precision trade-offs, and validation against CPU-based simulations in astroparticle physics.

Contribution

It introduces GPU-accelerated methods for optical photon propagation in CORSIKA 8, analyzing their efficiency and accuracy compared to traditional CPU approaches.

Findings

GPU methods significantly improve simulation speed

Trade-offs between performance and precision are manageable

GPU acceleration achieves physical accuracy limited by experimental resolution

Abstract

AI accelerators have proliferated in data centers in recent years and are now almost ubiquitous. In addition, their computational power and, most importantly, their energy efficiency are up to orders of magnitude higher than that of traditional computing. Over the last years, various methods and optimizations have been tested to use these hybrid systems for simulations in the context of astroparticle physics utilizing CORSIKA. The main focus of this talk is the propagation of optical, i.e. fluorescence and Cherenkov, photons through low density inhomogeneous media in the context of the next generation CORSIKA8 simulation framework. Different techniques used and approximations, e.g. the atmospheric model, tested during the development will be presented. The trade-off between performance and precision allows the experiment to achieve its physical precision limited to the real resolution of the experiment and not invest power and time in vanishing precision gains. The additional comparison of classical CPU-based simulations with the new methods validates these methods and allows evaluation against a known baseline.