基于机器学习的标准单元延迟预测  

Prediction of Standard Cell Delay Based on Machine Learning

作　　者：王永[1] 潘洋 WANG Yong;PAN Yang(School of Integrated Circuits,Shandong University)

机构地区：[1]山东大学集成电路学院

出　　处：《中国集成电路》2025年第1期75-80,共6页China lntegrated Circuit

基　　金：国家重点研发计划(No.2021YFA1003600);国家自然科学基金(No.U23A20348)。

摘　　要：随着半导体技术的快速发展和设计复杂性的增加,传统延迟计算方法越来越难以满足精确度和效率的需求,标准单元延迟预测在集成电路设计中就愈发重要。本文提出了一种基于机器学习的延迟预测方法,采用LightGBM算法对标准单元库中提取的数据进行建模。通过特征选择和优化,构建了能够有效捕捉延迟特性的预测模型。实验结果显示,与传统模型相比,基于LightGBM的方法在预测准确性和计算效率上展现出突出优势。该方法将机器学习算法与标准单元库设计相结合,利用机器学习模型,建立了延迟特性与电压、温度、输入传输延迟时间及输出负载等因素之间的映射关系,提供了一种快速、准确的标准单元延迟预测方案。此方法不仅提高了预测精度,还减少了计算时间,为标准单元延迟分析提供了一种创新解决方案,有望在实际芯片设计流程中发挥重要作用。With the rapid advancement of semiconductor technology and the increasing complexity of design,traditional delay calculation methods are increasingly unable to meet the requirements for accuracy and efficiency.Therefore,the prediction of standard cell delay has become increasingly important in integrated circuit design.This paper proposes a delay prediction method based on machine learning,using the LightGBM algorithm to model data extracted from a standard cell library.Through feature selection and optimization,a predictive model capable of effectively capturing delay characteristics is constructed.Experimental results show that compared to traditional models,the LightGBM-based approach demonstrates significant advantages in prediction accuracy and computational efficiency.This method combines machine learning algorithms with standard cell library design,using a machine learning model to establish the mapping relationship between delay characteristics and factors such as voltage,temperature,input transition time,and output load.It provides a fast and accurate solution for standard cell delay prediction.This approach not only improves prediction accuracy but also reduces computation time,offering an innovative solution for standard cell delay analysis and promising significant impact in practical chip design processes.

关 键 词：机器学习 标准单元延迟预测 静态时序分析 LightGBM 网格搜索优化 

分 类 号：TN4[电子电信—微电子学与固体电子学]