Hotspot Detection of Semiconductor Lithography Circuits Based on Convolutional Neural Network

作     者：Xingyu Zhou Youling Yu 

作者机构：Tongji UniversityShanghaiChina201804 

出 版 物：《Journal of Microelectronic Manufacturing》 (微电子制造学报（英文）)

年 卷 期：2018年第1卷第2期

页      面：31-38页

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

主　　题：lithography hotspot detection CNN deep learning 

摘      要：In the advanced semiconductor lithography manufacturing process,the sub-wavelength lithography gap may cause lithographic error and the difference between the wafer pattern and mask pattern which may cause wafer defects in the later *** if a layout passes the design rule checking(DRC),it still might contain process hotspots which are sensitive to the lithographic ***,process-hotspot detection has become a crucial *** this paper,we propose a convolutional neural network(CNN)based process-hotspot detection *** network parameters including the training batch size,learning rate,loss functions as well as the optimization methods are compared and the optimal method is proposed with respect to a typical *** results of the tuned model are better than common machine learning methods.A general training flow is *** method is flexible and can be applied to different benchmarks for better hotspot detection performance.