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FPGA-based tracking for the CMS Level-1 trigger using the tracklet algorithm
The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High-Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charge...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1748-0221/15/06/P06024 http://cds.cern.ch/record/2696252 |
Sumario: | The high instantaneous luminosities expected following the upgrade of the Large Hadron Collider (LHC) to the High-Luminosity LHC (HL-LHC) pose major experimental challenges for the CMS experiment. A central component to allow efficient operation under these conditions is the reconstruction of charged particle trajectories and their inclusion in the hardware-based trigger system. There are many challenges involved in achieving this: a large input data rate of about 20–40 Tb/s processing a new batch of input data every 25 ns, each consisting of about 15,000 precise position measurements and rough transverse momentum measurements of particles (“stubs”); performing the pattern recognition on these stubs to find the trajectories; and producing the list of trajectory parameters within 4 μs. This paper describes a proposed solution to this problem, specifically, it presents a novel approach to pattern recognition and charged particle trajectory reconstruction using an all-FPGA solution. The results of an end-to-end demonstrator system, based on Xilinx Virtex-7 FPGAs, that meets timing and performance requirements are presented along with a further improved, optimized version of the algorithm together with its corresponding expected performance. |
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