Abstract
AbstractWe describe a fully GPU-based implementation of the first level trigger for the upgrade of the LHCb detector, due to start data taking in 2021. We demonstrate that our implementation, named Allen, can process the 40 Tbit/s data rate of the upgraded LHCb detector and perform a wide variety of pattern recognition tasks. These include finding the trajectories of charged particles, finding proton–proton collision points, identifying particles as hadrons or muons, and finding the displaced decay vertices of long-lived particles. We further demonstrate that Allen can be implemented in around 500 scientific or consumer GPU cards, that it is not I/O bound, and can be operated at the full LHC collision rate of 30 MHz. Allen is the first complete high-throughput GPU trigger proposed for a HEP experiment.
Funder
European Research Council
Deutsche Forschungsgemeinschaft
National Science Foundation
Russian Science Foundation
Publisher
Springer Science and Business Media LLC
Subject
Nuclear and High Energy Physics,Computer Science (miscellaneous),Software
Reference25 articles.
1. LHCb collaboration, Aaij R, et al. (2015) LHCb detector performance. Int J Mod Phys A30: 1530022
2. Fitzpatrick C, Gligorov VV (2014) Anatomy of an upgrade event in the upgrade era, and implications for the lhcb trigger. Technical report LHCb-PUB-2014-027. CERN-LHCb-PUB-2014-027, CERN, Geneva
3. Aaij R et al (2016) Tesla: an application for real-time data analysis in high energy physics. Comput Phys Commun 208:35
4. Aaij R et al (2019) A comprehensive real-time analysis model at the LHCb experiment. JINST 14:P04006
5. LHCb Collaboration (2018) Computing Model of the Upgrade LHCb experiment. Technical report. CERN-LHCC-2018-014. LHCB-TDR-018, CERN, Geneva
Cited by
43 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献