Eschle, J;
Gál, T;
Giordano, M;
Gras, P;
Hegner, B;
Heinrich, L;
Hernandez Acosta, U;
... Vassilev, V; + view all
(2023)
Potential of the Julia Programming Language for High Energy Physics Computing.
Computing and Software for Big Science
, 7
, Article 10. 10.1007/s41781-023-00104-x.
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Abstract
Research in high energy physics (HEP) requires huge amounts of computing and storage, putting strong constraints on the code speed and resource usage. To meet these requirements, a compiled high-performance language is typically used; while for physicists, who focus on the application when developing the code, better research productivity pleads for a high-level programming language. A popular approach consists of combining Python, used for the high-level interface, and C++, used for the computing intensive part of the code. A more convenient and efficient approach would be to use a language that provides both high-level programming and high-performance. The Julia programming language, developed at MIT especially to allow the use of a single language in research activities, has followed this path. In this paper the applicability of using the Julia language for HEP research is explored, covering the different aspects that are important for HEP code development: runtime performance, handling of large projects, interface with legacy code, distributed computing, training, and ease of programming. The study shows that the HEP community would benefit from a large scale adoption of this programming language. The HEP-specific foundation libraries that would need to be consolidated are identified.
| Type: | Article |
|---|---|
| Title: | Potential of the Julia Programming Language for High Energy Physics Computing |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s41781-023-00104-x |
| Publisher version: | https://doi.org/10.1007/s41781-023-00104-x |
| Language: | English |
| Additional information: | This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| UCL classification: | UCL |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10215100 |
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