FPGA-based real-time charged particle trajectory reconstruction at the large hadron collider

Edward Bartz, Jorge Chaves, Yuri Gershtein, Eva Halkiadakis, Michael Hildreth, Savvas Kyriacou, Kevin Lannon, Anthony Lefeld, Anders Ryd, Louise Skinnari, Robert Stone, Charles Strohman, Zhengcheng Tao, Brian Winer, Peter Wittich, Zhiru Zhang, Margaret Zientek

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The upgrades of the Compact Muon Solenoid particle physics experiment at CERN's Large Hadron Collider provide a major challenge for the real-time collision data selection. This paper presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The challenges include a large input data rate of about 20 to 40~Tbps, processing a new batch of input data every 25~ns, each consisting of about 10,000 precise position measurements of particles ('stubs'), perform the pattern recognition on these stubs to find the trajectories, and produce the list of parameters describing these trajectories within 4~us. A proposed solution to this problem is described, in particular, the implementation of the pattern recognition and particle trajectory determination using an all-FPGA system. The results of an end-to-end demonstrator system based on Xilinx Virtex-7 FPGAs that meets timing and performance requirements are presented.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages64-71
Number of pages8
ISBN (Electronic)9781538640364
DOIs
StatePublished - Jun 30 2017
Event25th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017 - Napa, United States
Duration: Apr 30 2017May 2 2017

Publication series

NameProceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017

Other

Other25th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017
CountryUnited States
CityNapa
Period4/30/175/2/17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software
  • Hardware and Architecture
  • Computer Science Applications

Keywords

  • Detectors
  • Field programmable gate arrays
  • Hardware
  • High energy physics instrumentation computing
  • L1 track trigger
  • LHC environment
  • Particle physics
  • Pattern recognition
  • Physics computing
  • Trigger circuits

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  • Cite this

    Bartz, E., Chaves, J., Gershtein, Y., Halkiadakis, E., Hildreth, M., Kyriacou, S., Lannon, K., Lefeld, A., Ryd, A., Skinnari, L., Stone, R., Strohman, C., Tao, Z., Winer, B., Wittich, P., Zhang, Z., & Zientek, M. (2017). FPGA-based real-time charged particle trajectory reconstruction at the large hadron collider. In Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017 (pp. 64-71). [7966650] (Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FCCM.2017.27