EDGE: DBMS-Empowered Boolean Decomposition for GIG Synthesis

Boolean decomposition is a powerful technique in logic synthesis that breaks down Boolean functions into simpler components. Decomposition-based logic synthesis yields high-quality results and is particularly effective when combined with small-window optimization methods in Gate-Inverter Graphs (GIG). However, the efficiency limitations of current methods have constrained their applicability in handling large and complex logic. To address this challenge, we propose a novel framework, called EDGE, which leverages modern database techniques to accelerate Boolean decomposition, thereby achieving improved synthesis results while maintaining high efficiency. Experimental results demonstrate a runtime speedup of up to $21 \times$ and an overall reduction in node count of at least $15 \%$ compared to state-of-the-art synthesis methods.

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Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11133306
Primary Topic
Mathematics, Computing, and Information Processing
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article
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EDGE: DBMS-Empowered Boolean Decomposition for GIG Synthesis

Jianliang Xu, Xuliang Zhu, Mingxuan Yuan, Lei Chen et al.
Mathematics, Computing, and Information Processing
article

EDGE: DBMS-Empowered Boolean Decomposition for GIG Synthesis

Jianliang Xu, Xuliang Zhu, Mingxuan Yuan, Lei Chen, Xinyi Zhang, Xing Li, Ruofei Tang
article en

Abstract

Boolean decomposition is a powerful technique in logic synthesis that breaks down Boolean functions into simpler components. Decomposition-based logic synthesis yields high-quality results and is particularly effective when combined with small-window optimization methods in Gate-Inverter Graphs (GIG). However, the efficiency limitations of current methods have constrained their applicability in handling large and complex logic. To address this challenge, we propose a novel framework, called EDGE, which leverages modern database techniques to accelerate Boolean decomposition, thereby achieving improved synthesis results while maintaining high efficiency. Experimental results demonstrate a runtime speedup of up to $21 \times$ and an overall reduction in node count of at least $15 \%$ compared to state-of-the-art synthesis methods.

Hong Kong Baptist University (HK), Shanghai Jiao Tong University (CN), Huawei Technologies (China) (CN)
Openalex Percentile: Top 74%
Mathematics, Computing, and Information Processing
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EDGE: DBMS-Empowered Boolean Decomposition for GIG Synthesis — Jianliang Xu, Xuliang Zhu, et al. · (2025) | TGRS Research Map | TGRS