| Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 6 | |
| Section | T1 - Online computing | |
| DOI | https://doi.org/10.1051/epjconf/201921401003 | |
| Published online | 17 September 2019 | |
https://doi.org/10.1051/epjconf/201921401003
Kalman Filter track reconstruction on FPGAs for acceleration of the High Level Trigger of the CMS experiment at the HL-LHC
Imperial College London
* e-mail: sioni.summers10@imperial.ac.uk
Published online: 17 September 2019
Track reconstruction at the CMS experiment uses the Combinatorial Kalman Filter. The algorithm computation time scales exponentially with pileup, which will pose a problem for the High Level Trigger at the High Luminosity LHC. FPGAs, which are already used extensively in hardware triggers, are becoming more widely used for compute acceleration. With a combination of high performance, energy efficiency, and predictable and low latency, FPGA accelerators are an interesting technology for high energy physics. Here, progress towards porting of the CMS track reconstruction to Maxeler Technologies’ Dataflow Engines is shown, programmed with their high level language MaxJ. The performance is compared to CPUs, and further steps to optimise for the architecture are presented.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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