Polyglot Jet Finding

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 cl...

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Published inEPJ Web of conferences Vol. 295; p. 5017
Main Authors Stewart, Graeme Andrew, Gras, Philippe, Hegner, Benedikt, Krasnopolski, Atell
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 01.01.2024
Subjects
Algorithms
Clustering
Ergonomics
Languages
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ISSN2100-014X
2101-6275
2100-014X
DOI10.1051/epjconf/202429505017

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Summary: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.
Bibliography:ObjectType-Conference Proceeding-1
SourceType-Conference Papers & Proceedings-1
content type line 21
ISSN:2100-014X
2101-6275
2100-014X
DOI:10.1051/epjconf/202429505017