Kalman filter tracking on parallel architectures

G. Cerati, P. Elmer, S. Krutelyov, S. Lantz, M. Lefebvre, K. McDermott, D. Riley, M. Tadel, P. Wittich, F. Wurthwein, A. Yagil

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

We report on the progress of our studies towards a Kalman filter track reconstruction algorithm with optimal performance on manycore architectures. The combinatorial structure of these algorithms is not immediately compatible with an efficient SIMD (or SIMT) implementation; the challenge for us is to recast the existing software so it can readily generate hundreds of shared-memory threads that exploit the underlying instruction set of modern processors. We show how the data and associated tasks can be organized in a way that is conducive to both multithreading and vectorization. We demonstrate very good performance on Intel Xeon and Xeon Phi architectures, as well as promising first results on Nvidia GPUs.

Original languageEnglish (US)
Article number042051
JournalJournal of Physics: Conference Series
Volume898
Issue number4
DOIs
StatePublished - Nov 23 2017
Event22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016 - San Francisco, United States
Duration: Oct 10 2016Oct 14 2016

All Science Journal Classification (ASJC) codes

  • General Physics and Astronomy

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