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dc.contributor.authorNgubiri, John
dc.contributor.authorVan Vliet, Mario
dc.date.accessioned2012-09-25T16:05:50Z
dc.date.available2012-09-25T16:05:50Z
dc.date.issued2007
dc.identifier.issn0302-9743 (Print)
dc.identifier.issn1611-3349 (Online)
dc.identifier.urihttp://hdl.handle.net/10570/685
dc.descriptionThe original publication is available at http:www.springerlink.comen_US
dc.description.abstractPerformance evaluation in multi-cluster processor co-allocation - like in many other parallel job scheduling problems - is mostly done by computing the average metric value for the entire job stream. This does not give a comprehensive understanding of the relative performance of the different jobs grouped by their characteristics. It is however the characteristics that affect how easy/hard jobs are to schedule. We, therefore, do not get to understand scheduler performance at job type level. In this paper, we study the performance of multi-cluster processor co-allocation for different job groups grouped by their size, components and widest component. We study their relative performance, sensitivity to parameters and how their performance is affected by the heuristics used to break them up into components. We show that the widest component use characteristic that most affects job schedulability. We also show that to get better performance, jobs should be broken up in such a way that the width of the widest component is minimized.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesLecture notes in computer science;
dc.relation.ispartofseries;Volume 4942/2008
dc.subjectCo-allocationen_US
dc.subjectGroupen_US
dc.subjectPerformanceen_US
dc.titleGroup-wise performance evaluation of processor co-allocation in multi-cluster systemsen_US
dc.typeConference paperen_US


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