Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 03053 | |
Number of page(s) | 8 | |
Section | T3 - Distributed computing | |
DOI | https://doi.org/10.1051/epjconf/201921403053 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921403053
Adoption of ARC-CE and HTCondor at GridKa Tier 1
Karlsruhe Institute of Technology (KIT),
Karlsruhe,
Germany
* e-mail: max.fischer@kit.edu
** e-mail: eileen.kuehn@kit.edu
*** e-mail: matthias.schnepf@kit.edu
**** e-mail: andreas.petzold@kit.edu
† e-mail: andreas.heiss@kit.edu
Published online: 17 September 2019
The GridKa Tier 1 data and computing center hosts a significant share of WLCG processing resources. Providing these resources to all major LHC and other VOs requires efficient, scalable and reliable cluster management. To satisfy this, GridKa has recently migrated its batch resources from CREAM-CE and PBS to ARC-CE and HTCondor. This contribution discusses the key highlights of the adoption of this middleware at the scale of a European Tier 1 center: As the largest WLCG Tier 1 using the ARC-CE plus HTCondor stack, GridKa is exemplary for migrating more than 20 000 cores over the time span of only a few weeks. Supporting multiple VOs, we have extensively studied the constraints and possibilities of scheduling jobs of vastly different requirements. We present a robust and maintainable optimization of resource utilization which still respects constraints desired by VOs. Furthermore, we explore the dynamic extension of our batch system, integrating cloud resources with a lightweight configuration mechanism.
© The Authors, published by EDP Sciences, 2019
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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