GPU Enhancement of the Trigger to Extend Physics Reach at the LHC

TL;DR

This paper explores using GPUs to enhance the LHC's trigger system, enabling faster, more efficient event selection and the reconstruction of long-lived particles in real-time, thereby extending physics discovery potential.

Contribution

It introduces a GPU-accelerated tracking algorithm for the LHC trigger, allowing real-time reconstruction of long-lived particles for the first time.

Findings

GPU-based tracking achieves real-time performance

Enhanced trigger efficiency for rare physics signals

Potential to discover new physics phenomena

Abstract

Significant new challenges are continuously confronting the High Energy Physics (HEP) experiments, in particular the two detectors at the Large Hadron Collider (LHC) at CERN, where nominal conditions deliver proton-proton collisions to the detectors at a rate of 40 MHz. This rate must be significantly reduced to comply with both the performance limitations of the mass storage hardware and the capabilities of the computing resources to process the collected data in a timely fashion for physics analysis. At the same time, the physics signals of interest must be retained with high efficiency. The quest for rare new physics phenomena at the LHC leads us to evaluate a Graphics Processing Unit (GPU) enhancement of the existing High-Level Trigger (HLT), made possible by the current flexibility of the trigger system, which not only provides faster and more efficient event selection, but also includes the possibility of new complex triggers that were not previously feasible. A new tracking algorithm is evaluated on a NVIDIA Tesla K20c GPU, allowing for the first time the reconstruction of long-lived particles at the tracker system in the trigger. Preliminary time performance and efficiency will be presented.