Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 07035 | |
Number of page(s) | 8 | |
Section | Facilities and Virtualization | |
DOI | https://doi.org/10.1051/epjconf/202429507035 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429507035
Optimization of opportunistic utilization of the ATLAS high-level trigger farm for LHC Run 3
1 University of Texas at Arlington, Arlington, USA
2 Stoney Brook University, New York, USA
3 CERN, Geneva, Switzerland
4 LMU, Munich, Germany
* Corresponding author: Ivan.Glushkov@cern.ch
Published online: 6 May 2024
The ATLAS Trigger and Data Acquisition (TDAQ) High Level Trigger (HLT) computing farm contains 120 000 CPU cores. These resources are critical for the online selection and collection of collision data in the ATLAS experiment during LHC operation. Since 2013, during a longer period of LHC inactivity, these resources are being used for offline event simulation via the “Simulation at Point One” project (Sim@P1). With the recent start of LHC Run 3 and the flat computing budget expected in the near future, finding ways to maximize resource utilization efficiency is of paramount importance. Recent improvements in the ATLAS software stack can potentially allow the utilization of the Sim@P1 even during LHC operation for the duration of the LHC inter-fill gaps. While previous papers on the Sim@P1 project emphasized the technical implementation details, the current contribution is presenting results of a variety of tests that led to the optimal configuration of the job submission infrastructure which would allow the use of Sim@P1 during LHC Run 3.
© The Authors, published by EDP Sciences, 2024
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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