Details

Autor(en) / Beteiligte

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

Titel

FPGA-Based Real-Time Charged Particle Trajectory Reconstruction at the Large Hadron Collider

Ist Teil von

• 2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), 2017, p.64-71

Ort / Verlag

IEEE

Erscheinungsjahr

2017

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• 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 μs. 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.