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 × and an overall reduction in node count of at least 15% compared to state-of-the-art synthesis methods.
| Original language | English |
|---|---|
| Title of host publication | 2025 62nd ACM/IEEE Design Automation Conference, DAC 2025 |
| Publisher | IEEE |
| Number of pages | 7 |
| ISBN (Electronic) | 9798331503048 |
| ISBN (Print) | 9798331503055 |
| DOIs | |
| Publication status | Published - 22 Jun 2025 |
| Event | 62nd ACM/IEEE Design Automation Conference, DAC 2025 - San Francisco, United States Duration: 22 Jun 2025 → 25 Jun 2025 |
Publication series
| Name | Proceedings - Design Automation Conference |
|---|---|
| ISSN (Print) | 0738-100X |
Conference
| Conference | 62nd ACM/IEEE Design Automation Conference, DAC 2025 |
|---|---|
| Country/Territory | United States |
| City | San Francisco |
| Period | 22/06/25 → 25/06/25 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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