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Software Training in HEP

  • Sudhir Malik
  • , Samuel Meehan
  • , Kilian Lieret
  • , Meirin Oan Evans
  • , Michel H. Villanueva
  • , Daniel S. Katz
  • , Graeme A. Stewart
  • , Peter Elmer
  • , Sizar Aziz
  • , Matthew Bellis
  • , Riccardo Maria Bianchi
  • , Gianluca Bianco
  • , Johan Sebastian Bonilla
  • , Angela Burger
  • , Jackson Burzynski
  • , David Chamont
  • , Matthew Feickert
  • , Philipp Gadow
  • , Bernhard Manfred Gruber
  • , Daniel Guest
  • Stephan Hageboeck, Lukas Heinrich, Maximilian M. Horzela, Marc Huwiler, Clemens Lange, Konstantin Lehmann, Ke Li, Devdatta Majumder, Judita Mamužić, Kevin Nelson, Robin Newhouse, Emery Nibigira, Scarlet Norberg, Arturo Sánchez Pineda, Mason Proffitt, Brendan Regnery, Amber Roepe, Stefan Roiser, Henry Schreiner, Oksana Shadura, Giordon Stark, Stephen Nicholas Swatman, Savannah Thais, Andrea Valassi, Stefan Wunsch, David Yakobovitch, Siqi Yuan
  • University of Puerto Rico-Mayaguez
  • European Organization for Nuclear Research
  • University of Munich
  • University of Sussex
  • University of Mississippi
  • University of Illinois Urbana-Champaign
  • Princeton University
  • University Paris-Sud
  • Siena College
  • University of Pittsburgh
  • DIBINEM, Alma Mater Studiorum, University of Bologna
  • Sezione INFN di Roma La Sapienza
  • University of California, Davis
  • Oklahoma State University
  • University of Massachusetts Amherst
  • Deutsches Elektronen-Synchrotron (DESY)
  • Center for Advanced Systems Understanding (CASUS)
  • Technische Universität Dresden
  • Humboldt-Universität zu Berlin
  • Humanoid Technologies Lab (H2T)
  • University of Zurich
  • Simon Fraser University
  • University of Washington
  • Rudjer Boskovic Institute
  • University of Valencia
  • University of Michigan, Ann Arbor
  • University of British Columbia
  • Universite de Strasbourg
  • Université de Savoie
  • University of Oklahoma
  • University of Nebraska Lincoln
  • University of California at Santa Cruz
  • University of Amsterdam
  • SingleStore, Inc.
  • Boston University

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The long-term sustainability of the high-energy physics (HEP) research software ecosystem is essential to the field. With new facilities and upgrades coming online throughout the 2020s, this will only become increasingly important. Meeting the sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required software skills fall into three broad groups. The first is fundamental and generic software engineering (e.g., Unix, version control, C++, and continuous integration). The second is knowledge of domain-specific HEP packages and practices (e.g., the ROOT data format and analysis framework). The third is more advanced knowledge involving specialized techniques, including parallel programming, machine learning and data science tools, and techniques to maintain software projects at all scales. This paper discusses the collective software training program in HEP led by the HEP Software Foundation (HSF) and the Institute for Research and Innovation in Software in HEP (IRIS-HEP). The program equips participants with an array of software skills that serve as ingredients for the solution of HEP computing challenges. Beyond serving the community by ensuring that members are able to pursue research goals, the program serves individuals by providing intellectual capital and transferable skills important to careers in the realm of software and computing, inside or outside HEP.

Original languageEnglish
Article number22
JournalComputing and Software for Big Science
Volume5
Issue number1
DOIs
StatePublished - Dec 2021
Externally publishedYes

Keywords

  • HEP
  • Software
  • Training

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