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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2025 62nd ACM/IEEE Design Automation Conference (DAC) s. 1 - 2
Hlavní autoři: Fu, Rongliang, Zhang, Ran, Zheng, Ziyang, Shi, Zhengyuan, Pu, Yuan, Huang, Junying, Xu, Qiang, Ho, Tsung-Yi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 22.06.2025
Témata:
Design automation
Feature extraction
Focusing
Integrated circuit modeling
Logic
Logic circuits
Merging
Optimization methods
Predictive models
Table lookup
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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