CERN Accelerating science

Article
Report number	arXiv:2006.14603
Title	Extension of the INFN Tier-1 on a HPC system
Author(s)	Boccali, Tommaso (INFN, Pisa) ; Dal Pra, Stefano (INFN, CNAF) ; Spiga, Daniele (INFN, Perugia) ; Ciangottini, Diego (INFN, Perugia) ; Zani, Stefano (INFN, CNAF) ; Bozzi, Concezio (INFN, Ferrara) ; De Salvo, Alessandro (INFN, Rome) ; Valassi, Andrea (CERN) ; Noferini, Francesco (INFN, Bologna) ; Agnello, Luca dell ; Stagni, Federico (CERN) ; Doria, Alessandra (INFN, Naples) ; Bonacorsi, Daniele (U. Bologna, DIFA)
Publication	2020
Imprint	2020-06-25
Number of pages	13
Note	13 pages
In:	EPJ Web Conf. 245 (2020) 09009
In:	24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.09009
DOI	10.1051/epjconf/202024509009
Subject category	hep-ex ; Particle Physics - Experiment ; physics.comp-ph ; Other Fields of Physics
Abstract	The INFN Tier-1 located at CNAF in Bologna (Italy) is a center of the WLCG e-Infrastructure, supporting the 4 major LHC collaborations and more than 30 other INFN-related experiments. After multiple tests towards elastic expansion of CNAF compute power via Cloud resources (provided by Azure, Aruba and in the framework of the HNSciCloud project), and building on the experience gained with the production quality extension of the Tier-1 farm on remote owned sites, the CNAF team, in collaboration with experts from the ALICE, ATLAS, CMS, and LHCb experiments, has been working to put in production a solution of an integrated HTC+HPC system with the PRACE CINECA center, located nearby Bologna. Such extension will be implemented on the Marconi A2 partition, equipped with Intel Knights Landing (KNL) processors. A number of technical challenges were faced and solved in order to successfully run on low RAM nodes, as well as to overcome the closed environment (network, access, software distribution, ... ) that HPC systems deploy with respect to standard GRID sites. We show preliminary results from a large scale integration effort, using resources secured via the successful PRACE grant N. 2018194658, for 30 million KNL core hours.
Copyright/License	preprint: (License: arXiv nonexclusive-distrib 1.0)

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