English

Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies

Distributed, Parallel, and Cluster Computing 2026-05-28 v3

Abstract

Drawing on ideas from continuous integration, we present concepts of an automated benchmarking pipeline for high performance applications. Customization and collaboration have been key design goals owing to the requirements of research-software development as a continuous community effort. We have extended our previous conceptual work on systematic benchmarking workflows with the functionality of user-agnostic operations as well as continuous benchmarking. This fosters reproducibility and re-use of benchmarking results to ensure sustainable technological progress. We provide software-engineering solutions to keep pace with the rapid evolution of both large-scale models and high-performance computing systems with a view towards the scientific domains of neuroscience and artificial intelligence.

Keywords

Cite

@article{arxiv.2604.15919,
  title  = {Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies},
  author = {Jan Vogelsang and Melissa Lober and Catherine Mia Schöfmann and José Villamar and Dennis Terhorst and Johanna Senk and Hans Ekkehard Plesser and Markus Diesmann and Susanne Kunkel and Anno C. Kurth},
  journal= {arXiv preprint arXiv:2604.15919},
  year   = {2026}
}

Comments

20 pages, 8 figures

R2 v1 2026-07-01T12:14:11.231Z