| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 02023 | |
| Number of page(s) | 8 | |
| Section | Online Computing | |
| DOI | https://doi.org/10.1051/epjconf/202429502023 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429502023
Preliminary Performance Study of an Alternative Calorimeter Clustering Solution for Allen in LHCb
Smart Society Research Group, Engineering Department, La Salle-Universitat Ramon Llull, Quatre Camins 30, 08022 Barcelona, Spain
* e-mail: nuria.valls@salle.url.edu
** e-mail: xavier.vilasis@salle.url.edu
*** e-mail: miriam.calvo@salle.url.edu
**** e-mail: elisabet.golobardes@salle.url.edu
Published online: 6 May 2024
The LHCb experiment has recently started a new period of data taking after a major upgrade in both software and hardware. One of the biggest challenges has been the migration of the first part of the trigger system into a parallel GPU architecture framework called Allen, which performs a partial reconstruction of most of the LHCb sub-detectors. In Allen, the reconstruction of the Electromagnetic Calorimeter (ECAL) sub-detector is used in many selection algorithms, but its efficiency is currently 10% lower than the full reconstruction performed in the second stage of the trigger. In this work, we present a preliminary performance study of an alternative ECAL reconstruction algorithm implemented in Allen that complements the current algorithm to maximise the reconstruction efficiency and also minimise the impact on the throughput rate.
© 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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