Polyglot Jet Finding

This paper is the source files for the CHEP2023 conference proceedings, to be published in EPJ Web of Conferences.

The README.md file contains detailed instructions for reproducing the results presented in the paper.

Abstract

The evaluation of new computing languages for a large community, like HEP,
involves comparison of many aspects of the languages' behaviour, ecosystem and
interactions with other languages. In this paper we compare a number of
languages using a common, yet non-trivial, HEP algorithm: the anti-$k_t$
clustering algorithm used for jet finding. We compare specifically the algorithm
implemented in Python (pure Python and accelerated with numpy and numba), and
Julia, with respect to the reference implementation in C++, from Fastjet. As
well as the speed of the implementation we describe the ergonomics of the
language for the coder, as well as the efforts required to achieve the best
performance, which can directly impact on code readability and sustainability