CERN Accelerating science

Article
Report number	arXiv:1505.03137
Title	Massively Parallel Computing at the Large Hadron Collider up to the HL-LHC
Author(s)	Lujan, Paul (Princeton U.) ; Halyo, Valerie (Princeton U.)
Publication	2015-09-14
Imprint	12 May 2015
Number of pages	14
Note	14 pages, 6 figures. Proceedings of 2nd International Summer School on Intelligent Signal Processing for Frontier Research and Industry (INFIERI2014), to appear in JINST. Revised version in response to referee comments
In:	JINST 10 (2015) C09003
In:	2nd International Summer School on: INtelligent Signal Processing for FrontIEr Research and Industry, Paris, France, 14 - 25 Jul 2014, pp.C09003
DOI	10.1088/1748-0221/2015/9/C09003
Subject category	Detectors and Experimental Techniques
Accelerator/Facility, Experiment	CERN LHC ; CMS
Project	CERN HL-LHC
Abstract	As the Large Hadron Collider (LHC) continues its upward progression in energy and luminosity towards the planned High-Luminosity LHC (HL-LHC) in 2025, the challenges of the experiments in processing increasingly complex events will also continue to increase. Improvements in computing technologies and algorithms will be a key part of the advances necessary to meet this challenge. Parallel computing techniques, especially those using massively parallel computing (MPC), promise to be a significant part of this effort. In these proceedings, we discuss these algorithms in the specific context of a particularly important problem: the reconstruction of charged particle tracks in the trigger algorithms in an experiment, in which high computing performance is critical for executing the track reconstruction in the available time. We discuss some areas where parallel computing has already shown benefits to the LHC experiments, and also demonstrate how a MPC-based trigger at the CMS experiment could not only improve performance, but also extend the reach of the CMS trigger system to capture events which are currently not practical to reconstruct at the trigger level.
Copyright/License	arXiv nonexclusive-distrib. 1.0

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