Abstract

The authors propose and evaluate an efficient hierarchical clustering and allocation algorithm that drastically reduces the interprocess communications cost while observing lower and upper bounds of utilization for the individual processors. They compare the algorithm with branch-and-bound-type algorithms that can produce allocations with minimal communication cost, and show a very encouraging time complexity/suboptimality tradeoff in favor of the algorithm, at least for a class of process clusters and their random combinations which it is believed occur naturally in distributed applications. The heuristic allocation is well suited for a changing environment, where processors may fail or be added to the system and where the workload patterns may change unpredictably and/or periodically.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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