Treffer: Performance of Julia for High Energy Physics Analyse

Title:
Performance of Julia for High Energy Physics Analyse
Authors:
Stanitzki, Marcel, Strube, Jan
Source:
Computing and software for big science 5(1), 10 (2021). doi:10.1007/s41781-021-00053-3
Publisher Information:
Springer International Publishing
Publication Year:
2021
Collection:
DESY Publication Database (PUBDB)
Subject Terms:
info:eu-repo/classification/ddc/004, performance, programming, data management, particle physics, multiprocessor, benchmark, High energy physics, Julia programming language, Data analysis, Multithreading
Subject Geographic:
DE
Document Type:
Fachzeitschrift article in journal/newspaper
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/issn/2510-2044; info:eu-repo/semantics/altIdentifier/issn/2510-2036; info:eu-repo/semantics/altIdentifier/arxiv/arXiv:2003.11952
Availability:
https://bib-pubdb1.desy.de/record/459886
https://bib-pubdb1.desy.de/search?p=id:%22PUBDB-2021-02805%22
Rights:
info:eu-repo/semantics/openAccess
Accession Number:
edsbas.3028CF96
Database:
BASE

Weitere Informationen

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.