Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

Giuseppe Cerati, Peter Elmer, Slava Krutelyov, Steven Lantz, Matthieu Lefebvre, Mario Masciovecchio, Kevin McDermott, Daniel Riley, Matevž Tadel, Peter Wittich, Frank Würthwein, Avi Yagil

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

Original languageEnglish (US)
Article number00006
JournalEPJ Web of Conferences
StatePublished - Aug 8 2017
EventWorkshop on Connecting the Dots/ Intelligent Trackers, CTD/WIT 2017 - Orsay, France
Duration: Mar 6 2017Mar 9 2017

All Science Journal Classification (ASJC) codes

  • General Physics and Astronomy


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