Speaker
Description
During the High Luminosity LHC, to maintain a managable trigger rate and achieve its physics goals,the CMS detector will need charged particle tracking at the hardware trigger level. The tracklet approach is a track-finding algorithm based on a road-search algorithm that has been implemented on commercially available FPGA technology. This algorithm has achieved high performance in track-finding and completes tracking within 3.4 \mus on a Xilinx Virtex-7 FPGA. An overview of the algorithm and its implementation on an FPGA are discussed and the results of an end-to-end demonstrator system that meets timing and performance requirements are presented.
Summary
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. We 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 pairs of 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~$\mu$s. 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. This is presented on behalf of the CMS Collaboration.
