Performance of Julia for High Energy Physics Analyses

Stanitzki, Marcel; Strube, Jan F.

doi:10.1007/s41781-021-00053-3

Performance of Julia for High Energy Physics Analyses

Journal Article · Fri Apr 09 00:00:00 EDT 2021 · Computing and Software for Big Science

DOI:https://doi.org/10.1007/s41781-021-00053-3· OSTI ID:1797923

Stanitzki, Marcel ^[1]; ^[2]

Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
Univ. of Oregon, Eugene, OR (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

We argue that the Julia programming language is a compelling alternative to currently more common 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++. Furthermore, 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.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1797923

Report Number(s):: PNNL-SA--151985

Journal Information:: Computing and Software for Big Science, Journal Name: Computing and Software for Big Science Journal Issue: 1 Vol. 5; ISSN 2510-2036

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Julia, a HEP dream comes true Gras, Philippe Zenodo https://doi.org/10.5281/zenodo.5106100	text	January 2021
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