| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01197 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/epjconf/202533701197 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701197
Efficient and fast container execution using image snapshotters
1 Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen PSI, Switzerland
2 CERN, Esplanade des Particules 1, 1211 Meyrin 23, Switzerland
* e-mail: clemens.lange@cern.ch
** e-mail: valentin.volkl@cern.ch
Published online: 7 October 2025
A large fraction of computing workloads in high-energy and nuclear physics is executed using software containers. For physics analysis use, such container images often have sizes of several gigabytes. Executing a large number of such jobs in parallel on different compute nodes efficiently, demands the availability and use of caching mechanisms and image loading techniques to prevent network saturation and significantly reduce startup time. Using the industry-standard containerd container runtime for pulling and running containers, enables the use of various so-called snapshotter plugins that “lazily” load container images. We present a quantitative comparison of the performance of the CVMFS, SOCI, and Stargz snapshotter plugins. Furthermore, we also evaluate the user-friendliness of such approaches and discuss how such seamlessly containerised workloads contribute to the reusability and reproducibility of physics analyses.
© The Authors, published by EDP Sciences, 2025
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