The major challenge posed by the high instantaneous luminosity in the High Luminosity LHC (HL-LHC) motivates efficient and fast reconstruction of charged particle tracks in a high pile-up environment. While there have been efforts to use modern techniques like vectorization to improve the existing classic Kalman Filter based reconstruction algorithms, Line Segment Tracking takes a fundamentally different approach by doing a bottom-up reconstruction of tracks. Small track stubs from adjoining detector regions are constructed, and then these track stubs that are consistent with typical track trajectories are successively linked. Since the production of these track stubs is localized, they can be made in parallel, which lends way into using architectures like GPUs and multi-CPUs to take advantage of the parallelism. The algorithm is implemented in the context of the CMS Phase-2 Tracker and runs on NVIDIA Tesla V100 GPUs. Good physics and timing performance has been obtained, and stepping stones for the future are elaborated.
@article{arxiv.2207.08207,
title = {Line Segment Tracking in the HL-LHC},
author = {Gavin Niendorf and Tres Reid and Peter Wittich and Peter Elmer and Bei Wang and Philip Chang and Yanxi Gu and Vyacheslav Krutelyov and Balaji Venkat Sathia Narayanan and Matevz Tadel and Emmanouil Vourliotis and Avi Yagil},
journal= {arXiv preprint arXiv:2207.08207},
year = {2022}
}
Comments
Connecting the Dots Workshop (CTD 2022) v2 : Implemented referee comments from internal review