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A spanning tree based recursive refinement algorithm for fast task mapping

机译:基于生成树的递归优化算法用于快速任务映射

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The early version of recursive refinement, an algorithm, for fast task mapping is reported in this paper. An intended application for this algorithm is dynamic load balancing on a parallel/distributed system, including a network of workstations. Since this requires a fast mapping, the algorithm restricts the range of tasks movement during optimization and maps groups of tasks to groups of PE's in each iteration. Tasks are allowed to be swapped only between the two partitions that comprise the parent partition from the previous iteration. More freedom of task movement is unnecessary because structural characteristics of the problem graph are used to guide the mapping. The groups are derived from a spanning tree that is constructed from the original problem graph and is used to identify the structural characteristics required for the algorithm. Experimental results show that the algorithm is able to achieve a mapping quality as good as that by another mapping scheme characteristic of a class of algorithms that require an order of magnitude more time.
机译:本文报道了递归优化的早期版本,一种用于快速任务映射的算法。该算法的预期应用是并行/分布式系统(包括工作站网络)上的动态负载平衡。由于这需要快速映射,因此算法会限制优化过程中任务移动的范围,并在每次迭代中将任务组映射到PE组。只能在上一次迭代的父分区组成的两个分区之间交换任务。不需要更大的任务移动自由度,因为问题图的结构特征用于指导映射。这些组是从生成树中得出的,该生成树是从原始问题图构建的,用于标识算法所需的结构特征。实验结果表明,该算法能够获得与需要更多时间一个数量级的一类算法的另一种映射方案特性相同的映射质量。

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