English

Reproducible Cross-border High Performance Computing for Scientific Portals

Distributed, Parallel, and Cluster Computing 2025-01-30 v1

Abstract

To reproduce eScience, several challenges need to be solved: scientific workflows need to be automated; the involved software versions need to be provided in an unambiguous way; input data needs to be easily accessible; High-Performance Computing (HPC) clusters are often involved and to achieve bit-to-bit reproducibility, it might be even necessary to execute the code on a particular cluster to avoid differences caused by different HPC platforms (and unless this is a scientist's local cluster, it needs to be accessed across (administrative) borders). Preferably, to allow even inexperienced users to (re-)produce results, all should be user-friendly. While some easy-to-use web-based scientific portals support already to access HPC resources, this typically only refers to computing and data resources that are local. By the example of two community-specific portals in the fields of biodiversity and climate research, we present a solution for accessing remote HPC (and cloud) compute and data resources from scientific portals across borders, involving rigorous container-based packaging of the software version and setup automation, thus enhancing reproducibility.

Keywords

Cite

@article{arxiv.2209.00596,
  title  = {Reproducible Cross-border High Performance Computing for Scientific Portals},
  author = {Kessy Abarenkov and Anne Fouilloux and Helmut Neukirchen and Abdulrahman Azab},
  journal= {arXiv preprint arXiv:2209.00596},
  year   = {2025}
}

Comments

Accepted at 2nd Workshop on Reproducible Workflows, Data Management, and Security. During eScience in Salt Lake City, Utah, USA. 11-14 October 2022

R2 v1 2026-06-28T00:35:05.208Z