Late Breaking Results: Hybrid Logic Optimization with Predictive Self-Supervision

Hybrid optimization is an emerging approach in logic synthesis, focusing on applying diverse optimization methods to different parts of a logic circuit. This paper analyzes the relationship between each vertex and its corresponding optimization method. We extract a subgraph centered on each vertex a...

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Bibliographic Details
Published in:	2025 62nd ACM/IEEE Design Automation Conference (DAC) pp. 1 - 2
Main Authors:	Fu, Rongliang, Zhang, Ran, Zheng, Ziyang, Shi, Zhengyuan, Pu, Yuan, Huang, Junying, Xu, Qiang, Ho, Tsung-Yi
Format:	Conference Proceeding
Language:	English
Published:	IEEE 22.06.2025
Subjects:	Design automation Feature extraction Focusing Integrated circuit modeling Logic Logic circuits Merging Optimization methods Predictive models Table lookup
Online Access:	Get full text
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Summary:	Hybrid optimization is an emerging approach in logic synthesis, focusing on applying diverse optimization methods to different parts of a logic circuit. This paper analyzes the relationship between each vertex and its corresponding optimization method. We extract a subgraph centered on each vertex and quantify the logic optimization results of these subgraphs as vertex features. Based on these features, we propose a circuit partitioning method to cluster the logic circuit, enabling the final optimized circuit to be constructed by merging clusters optimized with their respective methods. Additionally, we introduce a self-supervised prediction model to efficiently obtain vertex features. The experimental results targeting LUT mapping demonstrate that our method achieves improvements of 8.48 \% in area and 9.81% in delay compared to the state-of-the-art.
DOI:	10.1109/DAC63849.2025.11132399