Počet záznamů: 1
Efficient Multi-site Data Movement Using Constraint Programming for Data Hungry Science
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SYSNO ASEP 0435931 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Efficient Multi-site Data Movement Using Constraint Programming for Data Hungry Science Tvůrce(i) Zerola, Michal (UJF-V)
Lauret, J. (US)
Barták, R. (CZ)
Šumbera, Michal (UJF-V) RID, ORCID, SAICelkový počet autorů 4 Zdroj.dok. Journal of Physics Conference Series, 219 - 17th International Conference on Computing in High Energy and Nuclear Physics (CHEP09). - Bristol : IOP Publishing Ltd, 2010 / Gruntorad J. ; Lokajíček M. - ISSN 1742-6588 Rozsah stran 062069 Poč.str. 10 s. Forma vydání Tištěná - P Akce 17th International Conference on Computing in High Energy and Nuclear Physics (CHEP) Datum konání 21.05.2009-27.05.2009 Místo konání Prague Země CZ - Česká republika Typ akce WRD Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova Constraint Programming technique ; CP model Vědní obor RIV BG - Jaderná, atomová a mol. fyzika, urychlovače CEP LC07048 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy GA202/07/0079 GA ČR - Grantová agentura ČR Institucionální podpora UJF-V - RVO:61389005 UT WOS 000295102000268 DOI 10.1088/1742-6596/219/6/062069 Anotace For the past decade, HENP experiments have been heading towards a distributed computing model in an effort to concurrently process tasks over enormous data sets that have been increasing in size as a function of time. In order to optimize all available resources (geographically spread) and minimize the processing time, it is necessary to face also the question of efficient data transfers and placements. A key question is whether the time penalty for moving the data to the computational resources is worth the presumed gain. Onward to the truly distributed task scheduling we present the technique using a Constraint Programming (CP) approach. The CP technique schedules data transfers from multiple resources considering all available paths of diverse characteristic (capacity, sharing and storage) having minimum user's waiting time as an objective. We introduce a model for planning data transfers to a single destination (data transfer) as well as its extension for an optimal data set spreading strategy (data placement). Several enhancements for a solver of the CP model will be shown, leading to a faster schedule computation time using symmetry breaking, branch cutting, well studied principles from job-shop scheduling field and several heuristics. Pracoviště Ústav jaderné fyziky Kontakt Markéta Sommerová, sommerova@ujf.cas.cz, Tel.: 266 173 228 Rok sběru 2015
Počet záznamů: 1