AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
Gao, Jian, Cao, Weidong, Yang, Junyi, Zhang, Xuan
–arXiv.org Artificial Intelligence
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. Y et, 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, AnalogGenie, a Gen erat i ve e ngine for automatic design/discovery of Analog circuit topologies-the most challenging and creative task in the conventional manual design flow of analog ICs. 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. Semiconductor integrated circuits (ICs) are the foundational hardware cornerstone to advance many emerging technologies such as generative AI, 5G/6G, and quantum computing. The demand for and the scale of ICs are soaring to unprecedented levels with the ever-increasing information and computing workloads (e.g., training foundation models with billions of parameters) (Achiam et al., 2023). Thus, accelerating the design of advanced ICs is a key to sustaining the development of future technologies. Excitingly, recent breakthroughs in generative AI have presented transformative opportunities to expedite the conventional design flows of ICs. As an example, NVIDIA's ChipNeMo (Liu et al., 2023a), a powerful domain-adapted LLM, can rapidly generate valuable digital designs with just a few prompts.
arXiv.org Artificial Intelligence
Feb-28-2025