# A parallel algorithm for fast reconstruction of primary vertices on heterogeneous architectures

## TL;DR

This paper introduces a new algorithm for quickly and accurately reconstructing particle collision vertices in the LHCb experiment using parallel computing.

## Contribution

A novel parallel vertex reconstruction algorithm optimized for heterogeneous computing architectures is introduced.

## Key findings

- The algorithm uses cluster finding in trajectory projections and adaptive vertex fitting.
- Implementations on x86 and GPU architectures are discussed and optimized.
- Performance is evaluated using simulated data samples.

## Abstract

The physics programme of the LHCb experiment at the Large Hadron Collider requires an efficient and precise reconstruction of the particle collision vertices. The LHCb Upgrade detector relies on a fully software-based trigger with an online reconstruction rate of 30\documentclass[12pt]{minimal}
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\begin{document}$$~\textrm{MHz}$$\end{document}MHz, necessitating fast vertex finding algorithms. This paper describes a new approach to vertex reconstruction developed for this purpose. The algorithm is based on cluster finding within a histogram of the particle trajectory projections along the beamline and on an adaptive vertex fit. Its implementations and optimisations on x86 and GPU architectures and its performance on simulated samples are also discussed.