Massively Parallel Computing at the Large Hadron Collider up to the HL-LHC

TL;DR

This paper explores how massively parallel computing can enhance data processing and trigger algorithms at the LHC, especially for the upcoming HL-LHC, to handle increased event complexity efficiently.

Contribution

It presents the application of MPC algorithms to improve trigger performance and extend the capabilities of CMS in reconstructing events in real-time.

Findings

MPC techniques improve trigger processing speed.

MPC-based trigger extends event reconstruction reach.

Parallel computing benefits already observed in LHC experiments.

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.