计算机应用研究2025，Vol.42Issue(1)：1-10,10.DOI:10.19734/j.issn.1001-3695.2024.05.0171
基于神经网络的优化算法在EDA中应用研究进展
Advances of optimization algorithm via neural network computing for EDA
摘要
Abstract
In response to the increasing complexity of chip design,EDA tools and methods are also evolving.However,EDA needs to be coordinated to achieve optimal power,performance,and area,and it does not always guarantee an optimal solu-tion.The application of EDA tools in the circuit design stage,including logic synthesis,layout and verification,belongs to the nonlinear programming solution process with multiple objectives and constraints.To better address the uncertainties of the solu-tion and the problems such as the easy to appear local extreme values,optimization algorithms based on neural network had been integrated into the design process of EDA tools.This paper first gave a brief overview of the optimization problem,multi-objective optimization calculation and optimization algorithm based on neural network in EDA,and then sorted out the optimi-zation solution methods of optimization algorithm based on neural network in different design stages such as logic synthesis,layout and verification,and expounded on the challenges and opportunities faced by the current research institute.It hoped to provide reference for automated integrated circuit design and related research.关键词
电子设计自动化/非线性规划/多目标优化/神经网络/优化计算Key words
electronic design automation(EDA)/nonlinear programming/multi-objective optimization/neural network/op-timization calculation分类
计算机与自动化引用本文复制引用
赵晨晖,贺珊,刘先明,郭东辉..基于神经网络的优化算法在EDA中应用研究进展[J].计算机应用研究,2025,42(1):1-10,10.基金项目
国家自然科学基金重点项目(61836010) （61836010）
福建省科技创新平台项目(2023-P-008) （2023-P-008）
