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arXiv:2003.11952physics.comp-ph

Performance of Julia for High Energy Physics Analyses

Marcel Stanitzki, Jan Strube

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Abstract

We argue that the Julia programming language is a compelling alternative to implementations in Python and C++ for common data analysis workflows in high energy physics. We compare the speed of implementations of different workflows in Julia with those in Python and C++. Our studies show that the Julia implementations are competitive for tasks that are dominated by computational load rather than data access. For work that is dominated by data access, we demonstrate an application with concurrent file reading and parallel data processing.

arXiv comments
16 pages, 4 pages, 1 table, 3 code listings
Journal reference
Computing and Software for Big Science (2021) 5:10
DOI
doi:10.1007/s41781-021-00053-3
Subjects
physics.comp-phComputational Physics hep-exHigh Energy Physics, Experiment

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  1. Rust Is Hard, Or: The Misery of Mainstream Programming 1 comment

    • Julia already is starting to be used for high energy physics (see https://arxiv.org/pdf/2003.11952.pdf and https://www.youtube.com/watch?v=QlfAa-LN1SA for details). It's definitely not the default yet, but there absolutely is effort to use it for particle accelerators.

      adgjlsfhk1View on HNParent context

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