Work Anomaly in Distributed Adaptive Partitioning Algorithms

Abstract

We investigate the parallel work redundancy of a class of adaptive algorithms, incurred from an increase in the total work required as the number of processes increases. The phenomenon is observed in adaptive integration algorithms, which are prototypical for methods that select and partition tasks from a distributed task pool. We show that, for some… (More)

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