Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
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Article Number | 05017 | |
Number of page(s) | 9 | |
Section | Sustainable and Collaborative Software Engineering | |
DOI | https://doi.org/10.1051/epjconf/202429505017 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429505017
Polyglot Jet Finding
1 CERN, Esplanade des Particules 1, Geneva, Switzerland
2 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3 Taras Shevchenko National University of Kyiv, Ukraine
* e-mail: graeme.andrew.stewart@cern.ch
Published online: 6 May 2024
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- kT 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.
© The Authors, published by EDP Sciences, 2024
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