A roadmap for HEP software and computing R&D for the 2020s

• Published in: Computing and software for big science Vol. 3; no. 7
• Main Authors: The HEP Software Foundation, Castro, Nuno Filipe
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing AG 01.12.2019; Springer International Publishing; Springer
• Subjects: Ciências Físicas; Ciências Naturais; Computing & software upgrade; Fysik; HL-LHC; Machine learning; Natural Sciences; Naturvetenskap; Original Article; Particle and Nuclear Physics; Particle physics; Physical Sciences; Physics; Physics and Astronomy; Software performance; Subatomic Physics; Subatomär fysik; Computing & software upgrade; Particle physics; Software performance; Machine learning; HL-LHC
• ISSN: 2510-2036; 2510-2044; 2510-2044
• DOI: 10.1007/s41781-018-0018-8

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.