LGARFeb 28, 2025

AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies

Tsinghua
arXiv:2503.00205v140 citationsh-index: 14Has CodeICLR
Originality Synthesis-oriented
AI Analysis

This work addresses the time-consuming manual design problem for analog IC engineers, offering a transformative approach with generative AI, though it appears incremental in applying existing AI techniques to a new domain.

The paper tackles the challenge of automating analog integrated circuit design by proposing AnalogGenie, a generative engine that builds a comprehensive dataset and scalable representation, resulting in broadening circuit variety, increasing device counts, and discovering unseen topologies beyond prior methods.

The massive and large-scale design of foundational semiconductor integrated circuits (ICs) is crucial to sustaining the advancement of many emerging and future technologies, such as generative AI, 5G/6G, and quantum computing. Excitingly, recent studies have shown the great capabilities of foundational models in expediting the design of digital ICs. Yet, applying generative AI techniques to accelerate the design of analog ICs remains a significant challenge due to critical domain-specific issues, such as the lack of a comprehensive dataset and effective representation methods for analog circuits. This paper proposes, $\textbf{AnalogGenie}$, a $\underline{\textbf{Gen}}$erat$\underline{\textbf{i}}$ve $\underline{\textbf{e}}$ngine for automatic design/discovery of $\underline{\textbf{Analog}}$ circuit topologies--the most challenging and creative task in the conventional manual design flow of analog ICs. AnalogGenie addresses two key gaps in the field: building a foundational comprehensive dataset of analog circuit topology and developing a scalable sequence-based graph representation universal to analog circuits. Experimental results show the remarkable generation performance of AnalogGenie in broadening the variety of analog ICs, increasing the number of devices within a single design, and discovering unseen circuit topologies far beyond any prior arts. Our work paves the way to transform the longstanding time-consuming manual design flow of analog ICs to an automatic and massive manner powered by generative AI. Our source code is available at https://github.com/xz-group/AnalogGenie.

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