Issue |
EPJ Web Conf.
Volume 150, 2017
Connecting The Dots/Intelligent Trackers 2017 (CTD/WIT 2017)
|
|
---|---|---|
Article Number | 00004 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/epjconf/201715000004 | |
Published online | 08 August 2017 |
https://doi.org/10.1051/epjconf/201715000004
L1 track trigger for the CMS HL-LHC upgrade using AM chips and FPGAs
Università di Pisa and INFN Pisa, Italy
e-mail: giacomo.fedi@cern.ch
Published online: 8 August 2017
The increase of luminosity at the HL-LHC will require the introduction of tracker information in CMS’s Level-1 trigger system to maintain an acceptable trigger rate when selecting interesting events, despite the order of magnitude increase in minimum bias interactions. To meet the latency requirements, dedicated hardware has to be used. This paper presents the results of tests of a prototype system (pattern recognition ezzanine) as core of pattern recognition and track fitting for the CMS experiment, combining the power of both associative memory custom ASICs and modern Field Programmable Gate Array (FPGA) devices. The mezzanine uses the latest available associative memory devices (AM06) and the most modern Xilinx Ultrascale FPGAs. The results of the test for a complete tower comprising about 0.5 million patterns is presented, using as simulated input events traversing the upgraded CMS detector. The paper shows the performance of the pattern matching, track finding and track fitting, along with the latency and processing time needed. The pT resolution over pT of the muons measured using the reconstruction algorithm is at the order of 1% in the range 3-100 GeV/c.
© The Authors, published by EDP Sciences, 2017
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.