1.南京邮电大学集成电路科学与工程学院,江苏南京 210023
2.复旦大学集成电路与微纳电子创新学院,上海 200433
3.香港大学计算与数据科学学院,香港 999077
王静 女,1997年11月出生于陕西省榆林市。博士毕业于复旦大学集成电路与微纳创新学院。现为南京邮电大学集成电路科学与工程学院讲师。主要研究方向为模拟集成电路设计及人工智能在设计自动化中的应用。中国电子学会会员编号:E190181919M。E-mail: wangjing25@njupt.edu.cn
林立宇 男,1995年11月出生于广东省揭阳市。现为复旦大学集成电路与微纳创新学院博士后。主要研究方向为数字集成电路设计。E-mail: lylin@fudan.edu.cn
李磊 男,1998年7月出生于江西省上饶市。现为香港大学计算与数据科学学院博士研究生。主要研究方向为多模态大模型。中国电子学会会员编号:E190160089A。E-mail: lilei98@connect.hku.hk
陈霖谊 女,2001年12月出生于四川省成都市。现为南京邮电大学集成电路科学与工程学院硕士研究生。主要研究方向为模拟集成电路设计。E-mail: 1225228011@njupt.edu.cn
李征 男,2001年4月出生于山东省临沂市。现为复旦大学集成电路与微纳电子创新学院硕士研究生。主要研究方向为近似计算与AI加速器设计。E-mail: 24212020117@m.fudan.edu.cn
来耀 男,1994年9月出生于安徽省芜湖市。博士毕业于香港大学计算与数据科学学院。现为剑桥大学博士后。主要研究方向为人工智能在设计自动化中的应用。E-mail: yl2204@cam.ac.u
李炎 男,1993年8月出生于江苏省无锡市。现为复旦大学集成电路与微纳创新学院青年研究员、博士生导师。主要研究方向为高可靠(抗辐射)/高性能(低温77 K)集成电路设计与方法学研究,在该领域已经发表论文20余篇。中国电子学会会员编号:E190029996S。E-mail: liyan@fudan.edu.cn
姚佳飞 男,1988年2月出生于江苏省常熟市。现为南京邮电大学副教授、博士生导师。主要研究方向为功率器件及集成封装技术。发表学术论文100余篇,授权中国发明专利60余项。中国电子学会会员编号:E190016854S。E-mail: jfyao@njupt.edu.cn
曾晓洋 男,1972年出生于湖南省衡阳市。现为复旦大学特聘教授、科学技术研究院副院长。主要研究方向为高能效系统芯片研究与开发。在该领域已经发表论文300余篇,申请发明专利100余项。中国电子学会会员编号:E190005669F。E-mail: xyzeng@fudan.edu.cn
郭宇锋 男,1974年4月出生于河南省洛阳市。现为南京邮电大学教授、博士生导师。主要研究方向为功率器件及其集成技术、宽禁带半导体技术、射频集成电路设计和智能EDA技术。发表学术论文400余篇,授权中国发明专利120余项。中国电子学会会员编号:E190004403F。E-mail: yfguo@njup.edu.cn
收稿:2025-12-23,
录用:2026-01-06,
纸质出版:2026-06-25
移动端阅览
王静, 林立宇, 李磊, 等. 大语言模型在电子设计自动化中的应用综述[J]. 电子学报, 2026, 54(06): 2377-2393.
WANG Jing, LIN Liyu, LI Lei, et al. A Survey on the Applications of Large Language Models in Electronic Design Automation[J]. Acta Electronica Sinica, 2026, 54(06): 2377-2393.
王静, 林立宇, 李磊, 等. 大语言模型在电子设计自动化中的应用综述[J]. 电子学报, 2026, 54(06): 2377-2393. DOI:10.12263/DZXB.20250971
WANG Jing, LIN Liyu, LI Lei, et al. A Survey on the Applications of Large Language Models in Electronic Design Automation[J]. Acta Electronica Sinica, 2026, 54(06): 2377-2393. DOI:10.12263/DZXB.20250971
随着集成电路设计复杂度呈指数级增长,传统电子设计自动化(Electronic Design Automation,EDA)工具面临着前所未有的挑战。近年来,大语言模型(Large Language Models,LLM)在自然语言处理领域取得的突破性进展为EDA领域带来了新的机遇。本文系统总结了LLM在EDA领域的应用研究,将其归纳为5个主要方向:寄存器传输级(Register Transfer Level,RTL)代码生成与优化、高层次综合与逻辑优化、后端实现验证与安全、模拟电路设计自动化,以及EDA工具流程自动化与辅助。本文同时总结了LLM在EDA领域所面临的挑战,包括高质量领域数据的稀缺性与多模态信息处理能力不足、EDA工具链的集成障碍等技术问题,以及知识产权风险、数据隐私保护和伦理合规性等应用层面的制约因素。未来研究方向主要集中在领域专用语料库的构建、跨模态信息融合的模型架构设计、标准化工具接口协议的制定,以及行业规范与伦理框架的建立等方面。
As the complexity of integrated circuit design grows exponentially
traditional electronic design automation (EDA) tools face unprecedented challenges. In recent years
breakthrough advances in large language models (LLMs) in the field of natural language processing have brought new opportunities to the EDA domain. This paper systematically reviews the application of LLMs in EDA
categorizing them into five main directions: register transfer level (RTL) code generation and optimization
high-level synthesis and logic optimization
physical implementation
verification and security
analog circuit design automation
and EDA tool flow automation and assistance. This paper also analyzes the main challenges faced by LLMs in the EDA domain
including technical issues such as scarcity of high-quality domain data and insufficient multimodal processing capabilities
heterogeneous tool chain integration barriers
and verification of generated content correctness and security
as well as application constraints including intellectual property risks
data privacy protection
and ethical compliance. Future research directions mainly focus on domain-specific corpus construction
cross-modal fusion model architecture
standardized tool interface protocols
and industry standards and ethical frameworks.
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