CBLO:用于网表分区的基于聚类的线性排序

K. Seong, C. Kyung
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引用次数: 1

摘要

提出了CBLO(基于聚类的线性排序)算法,该算法由全局排序和局部排序两部分组成。在全局排序中,算法从n个给定的顶点组成聚类,并对聚类进行排序。在局部排序中,每个簇中的元素是线性排序的。由此产生的线性顺序用于获得基于缩放成本目标函数的最优k-way划分。对k-way (2/spl les/k/spl les/10)划分的11个基准电路进行的实验表明,对于k-way缩放成本划分,该算法比MELO(多特征向量线性排序)平均提高10.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CBLO: a clustering based linear ordering for netlist partitioning
Proposes the CBLO (clustering-based linear ordering) algorithm, which consists of both global ordering and local ordering. In the global ordering, the algorithm forms clusters from n given vertices and orders the clusters. In the local ordering, the elements in each cluster are linearly ordered. The linear order thus produced is used to obtain optimal k-way partitioning based on a scaled cost objective function. Experiments with 11 benchmark circuits for k-way (2/spl les/k/spl les/10) partitioning showed that the proposed algorithm yields an average of 10.6% improvement over MELO (multiple-eigenvector linear ordering) for k-way scaled cost partitioning.
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