Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
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Article Number | 01031 | |
Number of page(s) | 6 | |
Section | 1 - Online and Real-time Computing | |
DOI | https://doi.org/10.1051/epjconf/202024501031 | |
Published online | 16 November 2020 |
https://doi.org/10.1051/epjconf/202024501031
The CMS Trigger Upgrade for the HL-LHC
Universidade Estadual Paulista – Unesp
* e-mail: Thiago.Tomei@cern.ch
Published online: 16 November 2020
The CMS experiment has been designed with a two-level trigger system: the Level-1 Trigger, implemented on custom-designed electronics, and the High Level Trigger, a streamlined version of the CMS offline reconstruction software running on a computer farm. During its second phase the LHC will reach a luminosity of 7.5 1034 cm−2 s−1 with a pileup of 200 collisions, producing integrated luminosity greater than 3000 fb−1 over the full experimental run. To fully exploit the higher luminosity, the CMS experiment will introduce a more advanced Level-1 Trigger and increase the full readout rate from 100 kHz to 750 kHz. CMS is designing an efficient data-processing hardware trigger that will include tracking information and high-granularity calorimeter information. The current Level-1 conceptual design is expected to take full advantage of advances in FPGA and link technologies over the coming years, providing a high-performance, low-latency system for large throughput and sophisticated data correlation across diverse sources. The higher luminosity, event complexity and input rate present an unprecedented challenge to the High Level Trigger that aims to achieve a similar efficiency and rejection factor as today despite the higher pileup and more pure preselection. In this presentation we will discuss the ongoing studies and prospects for the online reconstruction and selection algorithms for the high-luminosity era.
© The Authors, published by EDP Sciences, 2020
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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