DUNE Software and High Performance Computing

TL;DR

This paper discusses adapting DUNE's software to high-performance computing architectures, addressing challenges with data size and execution models to improve efficiency in large-scale physics experiments.

Contribution

It presents strategies for modifying existing software frameworks to better utilize modern HPC resources in the context of DUNE.

Findings

Identified key challenges in scaling DUNE software to HPC architectures

Proposed adaptation strategies for execution models and data handling

Outlined future directions for leveraging software frameworks in HPC environments

Abstract

DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by modern high-performance computing facilities. In order to efficiently exploit these new architectures, particularly those with high CPU core counts and GPU accelerators, our existing software execution models require adaptation. In addition, the large size of individual units of raw data from the far detector modules pose an additional challenge somewhat unique to DUNE. Here we describe some of these problems and how we begin to solve them today with existing software frameworks and toolkits. We also describe ways we may leverage these existing software architectures to attack remaining problems going forward. This whitepaper is a contribution to the Computational Frontier of Snowmass21.