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 Citation (Scopus)

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

Fingerprint

Colliding beam accelerators
Charged particles
Field programmable gate arrays (FPGA)
Trajectories
Pattern recognition
Position measurement
High energy physics
Solenoids
Processing
Experiments

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

Cite this

Bartz, E., Chaves, J., Gershtein, Y., Halkiadakis, E., Hildreth, M., Kyriacou, S., ... 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
Bartz, Edward ; Chaves, Jorge ; Gershtein, Yuri ; Halkiadakis, Eva ; Hildreth, Michael ; Kyriacou, Savvas ; Lannon, Kevin ; Lefeld, Anthony ; Ryd, Anders ; Skinnari, Louise ; Stone, Robert ; Strohman, Charles ; Tao, Zhengcheng ; Winer, Brian ; Wittich, Peter ; Zhang, Zhiru ; Zientek, Margaret. / FPGA-based real-time charged particle trajectory reconstruction at the large hadron collider. Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 64-71 (Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017).
@inproceedings{598011e3719d4749a2c650cde0b24797,
title = "FPGA-based real-time charged particle trajectory reconstruction at the large hadron collider",
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.",
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",
author = "Edward Bartz and Jorge Chaves and Yuri Gershtein and Eva Halkiadakis and Michael Hildreth and Savvas Kyriacou and Kevin Lannon and Anthony Lefeld and Anders Ryd and Louise Skinnari and Robert Stone and Charles Strohman and Zhengcheng Tao and Brian Winer and Peter Wittich and Zhiru Zhang and Margaret Zientek",
year = "2017",
month = "6",
day = "30",
doi = "10.1109/FCCM.2017.27",
language = "English (US)",
series = "Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "64--71",
booktitle = "Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017",
address = "United States",

}

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., 7966650, Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017, Institute of Electrical and Electronics Engineers Inc., pp. 64-71, 25th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017, Napa, United States, 4/30/17. https://doi.org/10.1109/FCCM.2017.27

FPGA-based real-time charged particle trajectory reconstruction at the large hadron collider. / Bartz, Edward; Chaves, Jorge; Gershtein, Yuri; Halkiadakis, Eva; Hildreth, Michael; Kyriacou, Savvas; Lannon, Kevin; Lefeld, Anthony; Ryd, Anders; Skinnari, Louise; Stone, Robert; Strohman, Charles; Tao, Zhengcheng; Winer, Brian; Wittich, Peter; Zhang, Zhiru; Zientek, Margaret.

Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 64-71 7966650 (Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017).

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

TY - GEN

T1 - FPGA-based real-time charged particle trajectory reconstruction at the large hadron collider

AU - Bartz, Edward

AU - Chaves, Jorge

AU - Gershtein, Yuri

AU - Halkiadakis, Eva

AU - Hildreth, Michael

AU - Kyriacou, Savvas

AU - Lannon, Kevin

AU - Lefeld, Anthony

AU - Ryd, Anders

AU - Skinnari, Louise

AU - Stone, Robert

AU - Strohman, Charles

AU - Tao, Zhengcheng

AU - Winer, Brian

AU - Wittich, Peter

AU - Zhang, Zhiru

AU - Zientek, Margaret

PY - 2017/6/30

Y1 - 2017/6/30

N2 - 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.

AB - 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.

KW - Detectors

KW - Field programmable gate arrays

KW - Hardware

KW - High energy physics instrumentation computing

KW - L1 track trigger

KW - LHC environment

KW - Particle physics

KW - Pattern recognition

KW - Physics computing

KW - Trigger circuits

UR - http://www.scopus.com/inward/record.url?scp=85027703176&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85027703176&partnerID=8YFLogxK

U2 - 10.1109/FCCM.2017.27

DO - 10.1109/FCCM.2017.27

M3 - Conference contribution

AN - SCOPUS:85027703176

T3 - Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017

SP - 64

EP - 71

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

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Bartz E, Chaves J, Gershtein Y, Halkiadakis E, Hildreth M, Kyriacou S et al. 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. Institute of Electrical and Electronics Engineers Inc. 2017. p. 64-71. 7966650. (Proceedings - IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2017). https://doi.org/10.1109/FCCM.2017.27