| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01099 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/epjconf/202533701099 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701099
Enhancements and resource optimisations for ATLAS use of HammerCloud
1 Fakultät für Physik, Ludwig-Maximilians-Universität München, München; Germany
2 Physikalisches Institut, Albert-Ludwigs-Universität Freiburg, Freiburg; Germany
* e-mail: a.lory@physik.lmu.de
Published online: 7 October 2025
HammerCloud (HC) is a framework for testing and benchmarking resources of the world wide LHC computing grid (WLCG). It tests the computing resources and the various components of distributed systems with workloads that can range from very simple functional tests to full-chain experiment workflows. This contribution concentrates on the ATLAS implementation, which makes extensive use of HC for monitoring global resources, and additionally, has implemented a mechanism to automatically exclude resources if certain critical tests fail. The auto-exclusion mechanism makes it possible to save resources by avoiding the submission of computationally intensive jobs to nonfunctioning clusters. However, in some cases central errors of the distributed computing system lead to massive exclusions of otherwise well-functioning resources. A new feature improves the recovery after such mass-exclusion events. For the auto-exclusion mechanism to be effective and save resources, test jobs need to be sent at a sufficient frequency which in turn also uses resources. In this contribution, we give an estimate of the total balance of resources of the auto-exclusion system and explore possible optimisations.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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