Working Time: 9:30-18:00
2025 The 10th International Conference on Integrated Circuits and Microsystems
    Email: icicm_conf@vip.163.com
    Secretary: Ms. Mila Xiao(肖老师)

Track 1: Emerging Techniques in Electronic Design Automation for Analog/Mixed-Signal ICs

模拟/混合信号集成电路电子设计自动化的新兴技术

Organizers / 组织者

Chair / 主席
Zhaori Bi 毕朝日
Fudan University, College of Integrated Circuits & Micro-Nano Electronics
复旦大学集成电路与微纳电子创新学院
Co-Chair / 共同主席
Keren Zhu 朱可人
Young Research Fellow, Fudan University
青年研究员,复旦大学

Abstract / 论坛简介

This special session explores transformative advancements in Electronic Design Automation (EDA) methodologies specifically tailored for analog/mixed-signal (AMS) integrated circuits. As modern AMS designs confront escalating challenges from nanometer-scale effects, heterogeneous integration, and stringent power-performance requirements, conventional EDA approaches often prove inadequate. The session will highlight four critical dimensions of innovation: (1) machine learning-enhanced simulation and modeling techniques that accelerate design convergence, (2) novel approaches for handling parasitics and variability in deep-submicron nodes, (3) co-design methodologies bridging analog front-ends with digital back-ends, and (4) signoff-quality verification for AMS circuits in hyperscale SoCs.

本专题论坛探讨针对模拟/混合信号集成电路的电子设计自动化(EDA)方法的突破性进展。随着现代AMS设计面临纳米级效应、异构集成和严格的功耗性能要求等日益严峻的挑战,传统EDA方法往往显得力不从心。本次论坛将重点展示四个关键创新方向:(1)加速设计收敛的机器学习增强仿真与建模技术,(2)处理深亚微米节点寄生效应和变异性的新方法,(3)连接模拟前端与数字后端的协同设计方法学,以及(4)超大规模SoC中AMS电路的签核质量验证技术。

Topics / 讨论主题

EDA for AMS ICs / AMS集成电路EDA
Machine Learning in EDA / EDA中的机器学习
Analog-Digital Co-Design / 模数混合协同设计
Variability-aware Design / 考虑变异性的设计