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A new fuzzy-clustering-based approach for two-way circuit partitioning

机译:一种新的双向电路分区基于基于模糊的聚类方法

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In this paper, a new fuzzy-clustering-based approach is proposed for two-way circuit partitioning. First, a circuit netlist is represented as an undirected edge-weighted graph by a tree net model. Furthermore, the fuzzy memberships and the clustering distance are introduced into the graph. Based on fuzzy c-means clustering, two groups of the fuzzy memberships will be assigned onto all of the vertices in the graph. Finally, according to these fuzzy memberships and the area information of the circuit netlist, the circuit netlist will be partitioned into two smaller netlists with area-balanced constraints. As a result, the proposed fuzzy clustering-based approach is implemented to obtain a better two-way partitioning with area-balanced constraints on circuit benchmarks.
机译:本文提出了一种新的基于模糊聚类的方法,用于双向电路分区。首先,电路网表由树网模型表示为无向边缘加权图。此外,模糊成员资格和聚类距离被引入图形中。基于模糊的C-Means聚类,将分配两组模糊成员资格,将分配到图表中的所有顶点上。最后,根据这些模糊的成员和电路网手册的区域信息,电路网表将被划分为两个具有区域平衡约束的较小网表。结果,实现了所提出的模糊聚类方法以获得在电路基准上的区域平衡约束的更好的双向分区。

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