CERN Accelerating science

CMS Note
Report number arXiv:2312.11728
Title Generalizing mkFit and its Application to HL-LHC
Author(s)

Cerati, Giuseppe (Fermilab) ; Elmer, Peter (Princeton U.) ; Gartung, Patrick (Fermilab) ; Giannini, Leonardo (San Diego, CASS ; UC, San Diego) ; Kortelainen, Matti (Fermilab) ; Krutelyov, Vyacheslav (San Diego, CASS ; UC, San Diego) ; Lantz, Steven (Cornell U., LNS) ; Masciovecchio, Mario (San Diego, CASS ; UC, San Diego) ; Reid, Tres (Cornell U., LNS) ; Reinsvold Hall, Allison (Naval Academy, Annapolis) ; Riley, Daniel (Cornell U., LNS) ; Tadel, Matevz (San Diego, CASS ; UC, San Diego) ; Vourliotis, Emmanouil (San Diego, CASS ; UC, San Diego) ; Wittich, Peter (Cornell U., LNS) ; Yagil, Avi (San Diego, CASS ; UC, San Diego)

Publication 2024
Imprint 29 Aug 2023
Number of pages 8
In: EPJ Web Conf. 295 (2024) 03019
In: 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023, pp.03019
DOI 10.1051/epjconf/202429503019
Subject category Detectors and Experimental Techniques ; Other Fields of Physics ; Particle Physics - Experiment
Accelerator/Facility, Experiment CERN LHC ; CMS
Abstract MkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline workflow of the CMS experiment. The CMS tracking performs a series of iterations, targeting reconstruction of tracks of increasing difficulty after removing hits associated to tracks found in previous iterations. MkFit has been adopted for several of the tracking iterations, which contribute to the majority of reconstructed tracks. When tested in the standard conditions for production jobs, speedups in track pattern recognition are on average of the order of 3.5x for the iterations where it is used (3-7x depending on the iteration). Multiple factors contribute to the observed speedups, including vectorization and a lightweight geometry description, as well as improved memory management and single precision. Efficient vectorization is achieved with both the icc and the gcc (default in CMSSW) compilers and relies on a dedicated library for small matrix operations, Matriplex, which has recently been released in a public repository. While the mkFit geometry description already featured levels of abstraction from the actual Phase-1 CMS tracker, several components of the implementations were still tied to that specific geometry. We have further generalized the geometry description and the configuration of the run-time parameters, in order to enable support for the Phase-2 upgraded tracker geometry for the HL-LHC and potentially other detector configurations. The implementation strategy and preliminary results with the HL-LHC geometry will be presented. Speedups in track building from mkFit imply that track fitting becomes a comparably time consuming step of the tracking chain. Prospects for an mkFit implementation of the track fit will also be discussed.
Copyright/License publication: (License: CC-BY-4.0)
preprint: (License: CC BY 4.0)



Corresponding record in: Inspire


 Datensatz erzeugt am 2023-09-25, letzte Änderung am 2024-11-03


Volltext:
CR2023_138 - Volltext herunterladenPDF
document - Volltext herunterladenPDF
370f51ee2dbcaf5c3b924369a92edb56 - Volltext herunterladenPDF
(zusätzliche Dateien)
Externer link:
Volltext herunterladenFermilab Library Server