Large Language Models for EDA: Future or Mirage?

作者：Zhuolun He, Yuan Pu, Haoyuan Wu, Tairu Qiu, Bei Yu · 发表于：ACM Transactions on Design Automation of Electronic Systems · 年份：2025 · DOI：10.1145/3736167 · 被引用次数：5 · 研究领域：Natural Language Processing Techniques、Topic Modeling、Speech Recognition and Synthesis

In this article, we explore the burgeoning intersection of large language models (LLMs) and electronic design automation (EDA). We critically assess whether LLMs represent a transformative future for EDA or merely a fleeting mirage. By organizing existing research into four critical domains of EDA—code generation, verification and debugging, knowledge representation and retrieval, and optimization/modeling—we provide a comprehensive overview of the current state-of-the-art. The survey concludes with a 5-level roadmap to guide the progressive integration and advancement of LLMs in EDA. Ultimately, this article aims to provide a comprehensive, evidence-based perspective on the role of LLMs in shaping the future of EDA.