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001     293114
005     20250730113828.0
024 7 _ |a 10.1016/j.jpdc.2014.08.001
|2 doi
024 7 _ |a 0743-7315
|2 ISSN
024 7 _ |a 1096-0848
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024 7 _ |a WOS:000346552500017
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024 7 _ |a altmetric:2688800
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024 7 _ |a inspire:1266150
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024 7 _ |a arXiv:1311.5904
|2 arXiv
024 7 _ |a openalex:W2106327684
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037 _ _ |a PUBDB-2016-00279
082 _ _ |a 004
088 _ _ |a arXiv:1311.5904
|2 arXiv
100 1 _ |a Aartsen, M. G.
|b 0
245 _ _ |a The IceProd framework: Distributed data processing for the IceCube neutrino observatory
260 _ _ |a Amsterdam [u.a.]
|c 2015
|b Elsevier
336 7 _ |a article
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336 7 _ |a Output Types/Journal article
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336 7 _ |a Journal Article
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336 7 _ |a ARTICLE
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336 7 _ |a JOURNAL_ARTICLE
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336 7 _ |a Journal Article
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500 _ _ |a (c) Elsevier Inc.
520 _ _ |a IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, identify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. This paper presents the first detailed description of IceProd, a lightweight distributed management system designed to meet these requirements. It is driven by a central database in order to manage mass production of simulations and analysis of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of computing resources, including grids and batch systems such as CREAM, HTCondor, and PBS. This is accomplished by a set of dedicated daemons that process job submission in a coordinated fashion through the use of middleware plugins that serve to abstract the details of job submission and job management from the framework.
536 _ _ |a 522 - High-energy neutrino astrophysics (POF2-522)
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700 1 _ |a Abbasi, R.
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700 1 _ |a Ackermann, Markus
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700 1 _ |a Adams, J.
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700 1 _ |a Arguelles, C.
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700 1 _ |a Auffenberg, J.
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700 1 _ |a Bai, X.
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700 1 _ |a Blumenthal, J.
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700 1 _ |a Boersma, D. J.
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700 1 _ |a Bohm, C.
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700 1 _ |a Böser, S.
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700 1 _ |a Desiati, P.
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700 1 _ |a de With, M.
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700 1 _ |a Eagan, R.
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700 1 _ |a Eisch, J.
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700 1 _ |a Kowalski, M.
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700 1 _ |a Pepper, J. A.
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700 1 _ |a Pérez de los Heros, C.
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773 _ _ |a 10.1016/j.jpdc.2014.08.001
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|t Journal of parallel and distributed computing
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787 0 _ |a Aartsen, M. G. et.al.
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Marc 21