# 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. 20222022022022022022202  
between multiple components. The existing circuit partition methods mainly represent the netlist in a hypergraph. Assuming a hypergraph has node set \(\mathbf{S}\) with \(K\) nodes, and edge (net) set \(\mathbf{E}\), partition methods aim to divide the \(K\) nodes into \(N\) subsets \(\mathbf{S}_{1},\mathbf{S}_{2},\ldots,\mathbf{S}_{N}\) with set size \(m_{1},m_{2},\ldots,m_{N}\), respectively. Most of the existing hypergraph-based partitioning methods were proposed before 20 years ago [3, 4]. Although a partition set can be obtained, the partition result is hard to effectively evaluate, and it is far from being applied in the practical application. With the development of electronic-aided design technology, the design process is more standardized, and potential patterns contained in the netlist are more regular. Inspired by the manual partitioning of physical modules, in this paper we focus on the potential features and attributes contained in the netlist, and propose a circuit module partitioning method based on the analysis of netlist network attributes and potential patterns. The partition algorithm takes the PCB netlist as input, and the module subsets as output. It is expected that these partition modules can not only be physically adjacent, but also functionally independent. The main contributions of this paper are as follows:  
1. The visualization analysis, attribute analysis, and pattern analysis of netlists are carried out, and the potential features and attributes in netlists are discovered. 2. Based on the potential features and attributes, a new approach to PCB netlist partition is proposed. The method first prepartitions the PCB netlist according to the network attributes, then presents three rules of classifying, matching, and force to redistribute the scattered components, and finally obtains the partition subsets. 3. The partition approach is evaluated on 11 netlists, outperforming the state of the arts on five different metrics. Experiments show that our approach based on network attributes and potential patterns can obtain 80-96% accuracy. A preliminary version of this work was published in [5]. This paper improves upon [5] in the following aspects: (1) the netlist visualization is studied to help netlist analysis, and inspires us to develop algorithms of partition; (2) some generic circuit patterns and repetitive patterns are analyzed, which is meaningful for netlist partition; (3) our algorithm is analyzed at each stage using different rules, and we report the evaluation indices to show the necessity of each stage. This paper is divided into six parts. Section 2 is the related research work. Section 3 discusses the discovery of potential patterns and analysis of network attributes in the netlist.