EPJ Web Conf.
Volume 251, 202125th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|Number of page(s)||9|
|Published online||23 August 2021|
Evolution of the energy efficiency of LHCb’s real-time processing
1 Nikhef National Institute for Subatomic Physics, Amsterdam, Netherlands
2 Universiteit Maastricht, Maastricht, Netherlands
3 European Organization for Nuclear Research (CERN), Switzerland
4 Department of Physics and Astronomy, University of Manchester, Manchester, United Kingdom
5 LPNHE, Sorbonne Université, CNRS/IN2P3, France
6 LIP6, Sorbonne Université, France
7 Massachusetts Institute of Technology, Cambridge, MA, United States
8 Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France
Published online: 23 August 2021
The upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4 TB/s in real time. Because LHCb’s physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this bandwidth challenge is equivalent to that of the ATLAS and CMS HL-LHC software read-out, but deliverable five years earlier. Over the past six years, the LHCb collaboration has undertaken a bottom-up rewrite of its software infrastructure, pattern recognition, and selection algorithms to make them better able to efficiently exploit modern highly parallel computing architectures. We review the impact of this reoptimization on the energy efficiency of the realtime processing software and hardware which will be used for the upgrade of the LHCb detector. We also review the impact of the decision to adopt a hybrid computing architecture consisting of GPUs and CPUs for the real-time part of LHCb’s future data processing. We discuss the implications of these results on how LHCb’s real-time power requirements may evolve in the future, particularly in the context of a planned second upgrade of the detector.
© The Authors, published by EDP Sciences, 2021
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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