这篇论文系统梳理了LLM在芯片前端设计中的应用，从HDL生成到设计空间探索，还介绍了OpenClaw等代理AI方案，适合关注EDA与AI结合的读者。
这篇论文讨论了LLM在电子设计自动化（EDA）前端设计中的应用，指出其可在HDL生成、测试台构建和设计空间探索等任务中作为统一接口。文章回顾了从局部辅助到自主代理执行的演变，并介绍了OpenClaw等先驱系统。还分析了LLM在电路生成和高级综合中提升设计质量的现有进展。最后，论文总结了集成LLM的关键挑战和未来机遇。
LLM for EDA in Front-End Design: Challenges and Opportunities
As chip complexity increases and time-to-market pressures grow, front-end design has become a critical bottleneck in chip development. Recently, Large Language Models (LLMs) have shown great potential in Electronic Design Automation (EDA). Beyond specification understanding, LLMs show the potential to serve as a unified intelligent interface for hardware description language (HDL) generation, testbench construction, and design space exploration. The rise of agentic AI, represented by pioneering systems such as OpenClaw, offers a strategic roadmap for the next generation EDA. From this perspective, this paper discusses the evolution of EDA from localized assistance to autonomous agentic execution. Then, we review representative advances of LLMs in front-end design, focusing on key tasks such as circuit and testbench generation from a shared specification, as well as design quality improvement in established workflows such as high-level synthesis. Finally, we discuss the key challenges and limitations of integrating LLMs into EDA, and outline future opportunities for advancing LLM-enabled front-end design, offering a systematic perspective for researchers interested in leveraging agentic AI technologies for EDA.