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Mastering Opportunistic Computing Resources for HEP

Schnepf, M. J.; Heidecker, C.; Fischer, M.; Giffels, M.; Kuehn, E.; Heiss, A.; Petzold, A.; Quast, G.

As results of the excellent LHC performance in 2016, more data than expected has been recorded leading to a higher demand for computing resources. It is already foreseeable that for the current and upcoming run periods a flat computing budget and the expected technology advance will not be sufficient to meet the future requirements. This results in a growing gap between supplied and demanded resources.
One option to reduce the emerging lack of computing resources is the utilization of opportunistic resources such as local university clusters, public and commercial cloud providers, HPC centers and volunteer computing. However, to use opportunistic resources additional challenges have to be tackled. At the Karlsruhe Institute of Technology (KIT) an infrastructure to dynamically use opportunistic resources is built up. In this paper tools, experiences, future plans and possible improvements are discussed.

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Verlagsausgabe §
DOI: 10.5445/IR/1000087758
Veröffentlicht am 23.11.2018
DOI: 10.1088/1742-6596/1085/3/032056
Seitenaufrufe: 48
seit 27.11.2018
Downloads: 27
seit 25.11.2018
Zugehörige Institution(en) am KIT Institut für Theoretische Teilchenphysik (TTP)
Steinbuch Centre for Computing (SCC)
Institut für Experimentelle Teilchenphysik (ETP)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 1742-6588, 1742-6596
KITopen-ID: 1000087758
HGF-Programm 53.52.02 (POF III, LK 02)
Erschienen in Journal of physics / Conference Series
Band 1085
Heft 3
Seiten Art. Nr.: 032056
Bemerkung zur Veröffentlichung 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT 2017; University of WashingtonSeattle; United States; 21 August 2017 through 25 August 2017
Nachgewiesen in Scopus
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