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

2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)(2017)

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摘要
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.
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关键词
particle physics,field programmable gate arrays,pattern recognition,hardware,detectors,LHC environment,physics computing,l1 track trigger,High energy physics instrumentation computing,trigger circuits
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