| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01302 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/epjconf/202533701302 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701302
GlideinBenchmark: Collecting resource information to optimize provisioning
1 Fermi National Accelerator Laboratory, PO Box 500, Batavia IL 60510-5011
2 Purdue University
* e-mail: marcom@fnal.gov
Published online: 7 October 2025
Choosing the right resource can speed up job completion, better utilize the available hardware, and visibly reduce costs, especially when renting computers in the cloud. This was demonstrated in earlier studies on HEP- Cloud. However, the benchmarking of the resources proved to be a laborious and time-consuming process. This paper presents GlideinBenchmark, a new Web application leveraging the pilot infrastructure of GlideinWMS to benchmark resources, and it shows how to use the data collected and published by GlideinBenchmark to automate the optimal selection of resources. An experiment can select the benchmark or the set of benchmarks that most closely evaluate the performance of its workflows. GlideinBenchmark, with the help of the GlideinWMS Factory, controls the benchmark execution. Finally, a scheduler like HEPCloud’s Decision Engine can use the results to optimize resource provisioning.
© 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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