Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

TL;DR

This paper evaluates the use of Kokkos, a portable programming model, to accelerate LArTPC detector simulations across diverse hardware architectures, aiming to balance performance and portability.

Contribution

It presents an assessment of Kokkos for portable, high-performance LArTPC simulations within the Wire-Cell Toolkit, addressing hardware diversity challenges.

Findings

Kokkos enables portable acceleration of LArTPC simulations.

Preliminary results show promising performance across architectures.

The approach reduces development effort for hardware-specific optimizations.

Abstract

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development that requires often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.