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Article
Title	Exploitation of HPC Resources for data intensive sciences
Author(s)	Girone, Maria (CERN) ; Southwick, David (CERN ; Iowa U.) ; Khristenko, Viktor (CERN) ; Medeiros, Miguel F (CERN) ; Giordano, Domenico (CERN) ; Høgstøyl, Ingvild Brevik (Norwegian U. Sci. Tech.) ; Atzori, Luca (CERN)
Publication	2021
Number of pages	9
In:	EPJ Web Conf. 251 (2021) 02042
In:	25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.02042
DOI	10.1051/epjconf/202125102042
Subject category	Computing and Computers
Abstract	The Large Hadron Collider (LHC) will enter a new phase beginning in 2027 with the upgrade to the High Luminosity LHC (HL-LHC). The increase in the number of simultaneous collisions coupled with a more complex structure of a single event will result in each LHC experiment collecting, storing, and processing exabytes of data per year. The amount of generated and/or collected data greatly outweighs the expected available computing resources. In this paper, we discuss effcient usage of HPC resources as a prerequisite for data-intensive science at exascale. First, we discuss the experience of porting CMS Hadron and Electromagnetic calorimeters reconstruction code to utilize Nvidia GPUs within the DEEP-EST project; second, we look at the tools and their adoption in order to perform benchmarking of a variety of resources available at HPC centers. Finally, we touch on one of the most important aspects of the future of HEP - how to handle the flow of petabytes of data to and from computing facilities, be it clouds or HPCs, for exascale data processing in a flexible, scalable and performant manner. These investigations are a key contribution to technical work within the HPC collaboration among CERN, SKA, GEANT and PRACE.
Copyright/License	publication: © The Authors, published by EDP Sciences, 2021 (License: CC-BY-4.0)

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