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URN: urn:nbn:de:swb:90-AAA1101043625
DOI: 10.1088/1742-6596/664/9/092008

High performance data analysis via coordinated caches

Fischer, M.; Metzlaff, C.; Kühn, E.; Giffels, M.; Quast, G.; Jung, C.; Hauth, T.

With the second run period of the LHC, high energy physics collaborations will have to face increasing computing infrastructural needs. Opportunistic resources are expected to absorb many computationally expensive tasks, such as Monte Carlo event simulation. This leaves dedicated HEP infrastructure with an increased load of analysis tasks that in turn will need to process an increased volume of data. In addition to storage capacities, a key factor for future computing infrastructure is therefore input bandwidth available per core. Modern data analysis infrastructure relies on one of two paradigms: data is kept on dedicated storage and accessed via network or distributed over all compute nodes and accessed locally. Dedicated storage allows data volume to grow independently of processing capacities, whereas local access allows processing capacities to scale linearly. However, with the growing data volume and processing requirements, HEP will require both of these features. For enabling adequate user analyses in the future, the KIT CMS group is merging both paradigms: popular data is spread over a local disk layer on compute nodes, whi ... mehr

Zugehörige Institution(en) am KIT Steinbuch Centre for Computing (SCC)
Institut für Kernphysik (IKP)
Publikationstyp Zeitschriftenaufsatz
Jahr 2015
Sprache Englisch
Identifikator ISSN: 1742-6588, 1742-6596
KITopen ID: 110104362
HGF-Programm 51.01.01; LK 01
Erschienen in Journal of physics / Conference Series
Band 664
Heft 9
Seiten 092008/1-8
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