Large Language Models for EDA: From Assistants to Agents

作者：Zhuolun He, Yuan Pu, Haoyuan Wu, Yuhan Qin, Tairu Qiu, Bei Yu · 发表于：Foundations and Trends® in Electronic Design Automation · 年份：2025 · DOI：10.1561/1000000063-2 · 被引用次数：3 · 研究领域：Natural Language Processing Techniques

This survey explores the application of Large Language Models (LLMs) in Electronic Design Automation (EDA), covering their roles as both assistants and autonomous agents. We review current research and practical implementations where LLMs are utilized for tasks such as question answering, script generation, and automated design processes. This work highlights the benefits of LLMs, including enhanced productivity and innovation, while also addressing challenges like accuracy and integration with traditional EDA tools. Furthermore, we discuss the evolution from LLMs as supportive assistants to more sophisticated agents capable of handling complex EDA workflows. This work aims to provide a comprehensive overview and guide future advancements in the integration of LLMs within the EDA domain.