PCB Network Analysis for Circuit Partitioning

Abstract

The complexity of automatic placement and routing is proportional to the scale of the circuit. Through netlist partition algorithms, printed circuit board (PCB) circuits are divided into different submodules, and the problem scale is effectively reduced in order to obtain the optimal automatic layout and routing. In this paper, we analyze net attributes and potential patterns in netlists through visualization, and propose a heuristic PCB netlist partition approach based on net attributes and potential patterns which we discover from netlists. Our partition approach takes the netlist as input, and module partition set as output. Firstly, the modules are prepartitioned using net attributes. Further, the special patterns in circuits are discovered, and the scattered resistors, capacitors, and other components caused by prepartitioning would be allocated to initial modules by three rules—classifying, matching, and force strategy. Our method is evaluated on 11 PCB netlists which are built manually. Experimental results show that our proposed netlist partition approach significantly outperforms the state of the art on all evaluation indices, which can achieve 80–96% partition accuracy.