Reproducible container solutions for codes and workflows in materials science

TL;DR

This paper introduces a reproducible, declarative software environment combining GNU Guix and Apptainer for materials science workflows, enabling reliable HPC computations and data analysis.

Contribution

It presents a novel integration of Guix and Apptainer for reproducible workflows in materials science, compatible with HPC and workflow managers.

Findings

Successful implementation of workflows for ab initio calculations and machine learning potentials.

Automated analysis of X-ray diffraction data at synchrotron facilities.

Demonstrated efficiency and reproducibility across multiple materials science applications.

Abstract

A computing solution combining the GNU Guix functional package manager with the Apptainer container system is presented. This approach provides fully declarative and reproducible software environments suitable for computational materials science. Its versatility and performance enable the construction of complete frameworks integrating workflow managers such as AiiDA, and Ewoks that can be deployed on HPC infrastructures. The efficiency of the solution is illustrated through several examples: (i) AiiDA workflows for automated dataset construction and analysis as well as path-integral molecular dynamics based on ab initio calculations; (ii) workflows for the training of machine-learning interatomic potentials; and (iii) an Ewoks workflow for the automated analysis of coherent X-ray diffraction data in large-scale synchrotron facilities. These examples demonstrate that the proposed environment provides a reliable and reproducible basis for computational and data-driven research in materials science.