Please use this identifier to cite or link to this item: https://doi.org/10.1109/CCGRID.2001.923257
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dc.titleDivisible load scheduling on a hypercube cluster with finite-size buffers and granularity constraints
dc.contributor.authorLi, X.
dc.contributor.authorVeeravalli, B.
dc.contributor.authorKo, C.C.
dc.date.accessioned2014-06-19T03:07:03Z
dc.date.available2014-06-19T03:07:03Z
dc.date.issued2001
dc.identifier.citationLi, X., Veeravalli, B., Ko, C.C. (2001). Divisible load scheduling on a hypercube cluster with finite-size buffers and granularity constraints. Proceedings - 1st IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2001 : 660-667. ScholarBank@NUS Repository. https://doi.org/10.1109/CCGRID.2001.923257
dc.identifier.isbn0769510108
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/69999
dc.description.abstractIn this paper we address the problem of scheduling a large size divisible load on a hypercube cluster of processors. Unlike in earlier studies in the divisible load theory (DLT) literature, here, we assume that the processors have finite-size buffers. Further we impose constraints on the extent to which the load can be divided, referred to as granularity constraint. We first present the closed-form solutions for the case with infinite-size buffers. For the case with load granularity constraint, we propose a simple algorithm to find the sub-optimal solution and then we analyze the case when these buffer are of finite size. For this case, we present an elegant strategy, referred to as incremental balancing strategy (IBS), to obtain an optimal load distribution. Based on the rigorous mathematical analysis, a number of interesting and useful properties exhibited by the algorithm are proven. Numerical examples are presented for the ease of understanding. © 2001 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CCGRID.2001.923257
dc.sourceScopus
dc.subjectcommunication delays
dc.subjectDivisible load theory
dc.subjectfinite-size buffel
dc.subjectgranularity
dc.subjecthypercube
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/CCGRID.2001.923257
dc.description.sourcetitleProceedings - 1st IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid 2001
dc.description.page660-667
dc.identifier.isiut000172837500094
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