Jul 9 – 13, 2018
Sofia, Bulgaria
Europe/Sofia timezone

CMS Computing Resources: Meeting the demands of the high-luminosity LHC physics program

Jul 12, 2018, 2:00 PM
Hall 7 (National Palace of Culture)

Hall 7

National Palace of Culture

presentation Track 3 – Distributed computing T3 - Distributed computing


David Lange (Princeton University (US))


The HL-LHC program has seen numerous extrapolations of its needed computing resources that each indicate the need for substantial changes if the desired HL-LHC physics program is to be supported within the current level of computing resource budgets. Drivers include large increases in event complexity (leading to increased processing time and analysis data size) and trigger rates needed (5-10 fold increases) for the HL-LHC program. CMS has recently undertaken an effort to merge the ideas behind short-term and long-term resource models in order to make easier and more reliable extrapolations to future needs. Near term computing resource estimation requirements depend on numerous parameters: LHC uptime and beam intensities; detector and online trigger performance; software performance; analysis data requirements; data access, management, and retention policies; site characteristics; and network performance. Longer term modeling is affected by the same characteristics, but with much larger uncertainties that must be considered to understand the most interesting handles for increasing the "physics per computing dollar" of the HL-LHC. In this presentation, we discuss the current status of long term modeling of the CMS computing resource needs for HL-LHC with emphasis on techniques for extrapolations, uncertainty quantification, and model results. We illustrate potential ways that high-luminosity CMS could accomplish its desired physics program within today's computing budgets.

Primary authors

David Lange (Princeton University (US)) Kenneth Bloom (University of Nebraska Lincoln (US)) Eric Vaandering (Fermi National Accelerator Lab. (US)) Oliver Gutsche (Fermi National Accelerator Lab. (US)) Tommaso Boccali (INFN Sezione di Pisa, Universita' e Scuola Normale Superiore, P)

Presentation materials