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Self-organizing Core Allocation

dc.contributor.authorZiermann, Tobias
dc.contributor.authorWildermann, Stefan
dc.contributor.authorTeich, Jürgen
dc.date.accessioned2017-12-06T09:07:46Z
dc.date.available2017-12-06T09:07:46Z
dc.date.issued2013
dc.description.abstractThis paper deals with the problem of dynamic allocation of cores to parallel applications on homogeneous many-core systems such as, for example, MultiProcessor System-on-Chips (MPSoCs). For a given number of thread-parallel applications, the goal is to find a core assignment that maximizes the average speedup. However, the difficulty is that some applications may have a higher speedup variation than others when assigned additional cores. This paper first presents a centralized algorithm to calculate an optimal assignment for the above objective. However, as the number of cores and the dynamics of applications will significantly increase in the future, decentralized concepts are necessary to scale with this development. Therefore, a decentralized (self-organizing) algorithm is developed in order to minimize the amount of global information that has to be exchanged between applications. The experimental results show that this approach can reach the optimal result of the centralized version in average by 98.95%.en
dc.identifier.doi10.1007/BF03354241
dc.identifier.pissn0177-0454
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/8608
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofPARS: Parallel-Algorithmen, -Rechnerstrukturen und -Systemsoftware: Vol. 30, No. 1
dc.relation.ispartofseriesPARS: Parallel-Algorithmen, -Rechnerstrukturen und -Systemsoftware
dc.subjectAverage Speedup
dc.subjectOptimal Assignment
dc.subjectCore Allocation
dc.subjectAdditional Core
dc.subjectSpeedup Function
dc.titleSelf-organizing Core Allocationen
dc.typeText/Journal Article
gi.citation.endPage101
gi.citation.startPage90

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