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arXiv:1910.09970

CMS NOTE -2019/005

FPGA-based tracking for the CMS Level-1 trigger using the tracklet algorithm

E. Bartz, G. Boudoul, R. Bucci, J. Chaves, E. Clement, D. Cranshaw, S. Dutta, Y. Gershtein, R. Glein, K. Hahn, E. Halkiadakis, M. Hildreth, S. Kyriacou, K. Lannon, A. Lefeld, Y. Liu, E. MacDonald, N. Pozzobon, A. Ryd, K. Salyer, P. Shields, L. Skinnari, K. Stenson, R. Stone, C. Strohman, K. Sung, Z. Tao, M. Trovato, K. Ulmer, S. Viret, B. Winer, P. Wittich, B. Yates, M. Zientek

The high instantaneous luminosities expected following the upgrade of theLHC to the HL-LHC pose major experimental challenges... 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 ..: 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 ... 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.