通过递归最小分割双分区将任务分配到超立方体上

F. Erçal, J. Ramanujam, P. Sadayappan
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引用次数: 154

摘要

为了将并行程序的任务有效映射到超立方并行计算机上,提出了一种基于Kernighan-Lin最小分割启发式的高效递归任务分配方案。通过与一种自适应、缩放模拟退火方法的比较,对该方法进行了评价。结果表明,递归分配方案在大量大型测试任务图上是有效的,其解的质量几乎与模拟退火方法相当,且计算时间比模拟退火方法少几个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Task allocation onto a hypercube by recursive mincut bipartitioning
An efficient recursive task allocation scheme, based on the Kernighan-Lin mincut bisection heuristic, is proposed for the effective mapping of tasks of a parallel program onto a hypercube parallel computer. It is evaluated by comparison with an adaptive, scaled simulated annealing method. The recursive allocation scheme is shown to be effective on a number of large test task graphs - its solution quality is nearly as good as that produced by simulated annealing, and its computation time is several orders of magnitude less.
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