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Subgraph matching-based reference placement for printed circuit board designs

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Abstract

Reference placement is promising to handle the increasing complexity in printed circuit board (PCB) designs, which aims to find the isomorphism of the placed template in component combination to reuse the placement. In this paper, we convert the netlist information into a graph and then model the reference placement as a subgraph matching problem. Since the state-of-the-art subgraph matching methods usually recursively search the solutions and suffer from high time and memory consumption in large-scale designs, we develop a novel subgraph matching algorithm D2BS with diversity tolerance and improved backtracking to guarantee matching quality and efficiency. The D2BS algorithm is founded on a data structure called the candidate space (CS) structure. We build and filter the candidate set for each query node according to our designed features to construct the CS structure. During the CS optimization process, a graph diversity tolerance strategy is adopted to achieve efficient inexact matching. Then, hierarchical matching is developed to search the template embeddings in the CS structure guided by branch backtracking and matched-node snatching strategies. Based on the industrial PCB designs, experimental results show that D2BS outperforms the state-of-the-art subgraph matching method in matching accuracy and running time.

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China under Grants 62104037 and 92373207 and the MOST of Taiwan under Grant MOST 110-2221-E-002-177-MY3.

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ZZ, YL, and MS gave the idea and wrote the main manuscript text. YL, MS, HS, and YX did the experiments. All authors reviewed the manuscript.

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Correspondence to Ziran Zhu.

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Preliminary version of this paper was presented at the 2022 ACM/IEEE Design Automation Conference (DAC’22), San Francisco, CA, USA, July 2022 [1].

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Zhu, Z., Li, Y., Su, M. et al. Subgraph matching-based reference placement for printed circuit board designs. J Supercomput (2024). https://doi.org/10.1007/s11227-024-06338-9

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