Software Training in HEP.

Q1 Computer Science Computing and Software for Big Science Pub Date : 2021-01-01 Epub Date: 2021-10-08 DOI:10.1007/s41781-021-00069-9
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
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引用次数: 4

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.

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HEP软件培训。
高能物理(HEP)研究软件生态系统的长期可持续性对该领域至关重要。随着新设施和升级在21世纪20年代上线,这只会变得越来越重要。迎接可持续发展的挑战,需要一支具备HEP领域知识和先进软件技能的员工队伍。所需的软件技能分为三大类。第一个是基本的和通用的软件工程(例如,Unix、版本控制、c++和持续集成)。第二是特定于领域的HEP包和实践的知识(例如,ROOT数据格式和分析框架)。第三是涉及专业技术的更高级的知识,包括并行编程、机器学习和数据科学工具,以及维护各种规模的软件项目的技术。本文讨论了由HEP软件基金会(HSF)和HEP软件研究与创新研究所(IRIS-HEP)领导的HEP集体软件培训计划。该计划为参与者提供一系列软件技能,作为解决HEP计算挑战的成分。除了通过确保成员能够追求研究目标来服务于社区之外,该计划还通过提供智力资本和可转移技能来服务于个人,这些技能对在HEP内外的软件和计算领域的职业很重要。
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来源期刊
Computing and Software for Big Science
Computing and Software for Big Science Computer Science-Computer Science (miscellaneous)
CiteScore
6.20
自引率
0.00%
发文量
15
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