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Non-contiguous processor allocation algorithms for distributed memory multicomputers
40
Citations
9
References
1994
Year
Cluster ComputingHeterogeneous ComputingDistributed Memory MulticomputersEngineeringComputer ArchitectureMultiple Buddy StrategyHigh-performance ArchitectureParallel ComputingManycore ProcessorMassively-parallel ComputingComputer EngineeringContiguous Allocation StrategiesComputer ScienceProcessor Allocation AlgorithmsDistributed ProcessingEdge ComputingParallel Performance EvaluationCloud ComputingMany-core ArchitectureMultiprocessor SystemParallel Programming
Current processor allocation techniques for highly parallel systems have thus far been restricted to contiguous allocation strategies for which performance suffers significantly due to the inherent problem of fragmentation. We are investigating processor allocation algorithms which lift the restriction on contiguity of processors in order to address the problem of fragmentation. Three non-contiguous processor allocation strategies: naive, random and the multiple buddy strategy (MBS) are proposed and studied in this paper. Simulations compare the performance of the non-contiguous strategies with that of several well-known contiguous algorithms. We show that non-contiguous allocation algorithms perform better overall than the contiguous ones, even when message-passing contention is considered. We also present the results of experiments on an Intel Paragon XP/S-15 with 208 nodes that show non-contiguous allocation is feasible with current technologies. >
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