Circuit clustering using graph coloring

We present a circuit clustering technique based on graph coloring. A given netlist is modeled as an undirected graph and its vertices are colored. Based on this coloring information and the notion of rank of a node and the number of adjacent unique colors it sees, we derive cost functions for the graph edges. We identify cliques in the graph and use these cliques, starting from the max_clique, as building blocks for our clusters. A cost function is derived using the cluster density notion and edge costs. Finally, we use this cost function to identify the critical edges, which when deleted, yield good clusters in the original circuit.

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