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Title: Potential of the Julia Programming Language for High Energy Physics Computing

Journal Article · · Computing and Software for Big Science
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4];  [5]; ORCiD logo [6]; ORCiD logo [7]; ORCiD logo [6]; ORCiD logo [8]; ORCiD logo [5]; ORCiD logo [9]; ORCiD logo [10]; ORCiD logo [11]; ORCiD logo [5]; ORCiD logo [6]; ORCiD logo [5]; ORCiD logo [12];  [11]
  1. University of Zurich (Switzerland)
  2. Friedrich-Alexander University Erlangen-Nuremberg, Bamberg (Germany)
  3. University College London (United Kingdom)
  4. University Paris-Saclay, Gif-sur-Yvette (France)
  5. European Organization for Nuclear Research (CERN), Geneva (Switzerland)
  6. Max-Planck-Institut für Physik, Munich (Germany)
  7. Center for Advanced Systems Understanding, Görlitz (Germany); Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany)
  8. Harvard University, Cambridge, MA (United States)
  9. ORIGINS Excellence Cluster, Garching (Germany); Ludwig Maximilian University of Munich, Munich (Germany)
  10. Universidad Antonio Nariño, Ibagué (Colombia)
  11. Princeton University, NJ (United States)
  12. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); University of Oregon, Eugene, OR (United States)
+ Show Author Affiliations

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.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
2300538
Report Number(s):
PNNL-SA-185647
Journal Information:
Computing and Software for Big Science, Vol. 7, Issue 1; ISSN 2510-2036
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English

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97 MATHEMATICS AND COMPUTING
Julia
HEP
Python
high energy and nuclear physics
programming language
HPC