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.
External IDs:dblp:conf/dac/TangZZCLYX25
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