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<p><b>Abstract</b>—Traditional multiprocessor scheduling schemes have been one of either space-sharing or time-sharing. Space-sharing schemes perform better than time-sharing at low to moderate system loads. However, they have a disadvantage of wasting processing power within partitions at medium to high system loads. Time sharing schemes tend to perform better at medium to high system loads. Almost all the scheduling schemes proposed so far have been tested under ad hoc workload considerations. In light of recent knowledge about workloads, it is imperative to develop an integrated scheduling scheme that combines the advantages of space- and time-sharing while overcoming their individual drawbacks. We propose such a scheduling scheme, called Hierarchical Scheduling Policy, which is efficient as well as general enough to accommodate multiple workloads. Simulation results indicate that our scheme significantly outperforms the best space- and time-sharing mechanisms at medium to high system loads even in the absence of knowledge regarding individual job characteristics. </p>
Multicomputer systems, job/task scheduling, space partitioning, time sharing, hierarchical scheduling, multiple workloads, performance evaluation.

S. Dandamudi and T. Thanalapati, "An Efficient Adaptive Scheduling Scheme for Distributed Memory Multicomputers," in IEEE Transactions on Parallel & Distributed Systems, vol. 12, no. , pp. 758-768, 2001.
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