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Online Scheduling on a CPU-GPU Cluster

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7876))

Abstract

We consider the online scheduling problem in a CPU-GPU cluster. In this problem there are two sets of processors, the CPU processors and GPU processors. Each job has two distinct processing times, one for the CPU processor and the other for the GPU processor. Once a job is released, a decision should be made immediately about which processor it should be assigned to. The goal is to minimize the makespan, i.e., the largest completion time among all the processors. Such a problem could be seen as an intermediate model between the scheduling problem on identical machines and unrelated machines. We provide a 3.85-competitive online algorithm for this problem and show that no online algorithm exists with competitive ratio strictly less than 2. We also consider two special cases of this problem, the balanced case where the number of CPU processors equals to that of GPU processors, and the one-sided case where there is only one CPU or GPU processor. We provide a \((1+\sqrt{3})\)-competitive algorithm for the balanced case, and a 3-competitive algorithm for the one-sided case.

Research was supported by in part by NSFC(11071215,11271325).

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Chen, L., Ye, D., Zhang, G. (2013). Online Scheduling on a CPU-GPU Cluster. In: Chan, TH.H., Lau, L.C., Trevisan, L. (eds) Theory and Applications of Models of Computation. TAMC 2013. Lecture Notes in Computer Science, vol 7876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38236-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-38236-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38235-2

  • Online ISBN: 978-3-642-38236-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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