基于预训练VGG11模型的光刻坏点检测方法  

Lithography Hotspot Detection Method Based on Pre-trained VGG11 Model

作　　者：廖陆峰 李思坤[1,2] 王向朝 Liao Lufeng;Li Sikun;Wang Xiangzhao(Laboratory of Information Optics and OptoElectronic Technology,Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800,China;Center of Materials Science and Optoelectronics Engineering,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院上海光学精密机械研究所信息光学与光电技术实验室,上海201800 [2]中国科学院大学材料与光电研究中心,北京100049

出　　处：《光学学报》2023年第3期132-141,共10页Acta Optica Sinica

基　　金：国家科技重大专项(2017ZX02101004-002,2017ZX02101004);国家自然科学基金(U22A2070)。

摘　　要：模型性能表现和模型训练时间影响着基于迁移学习坏点检测方法的应用,而选用模型和迁移学习策略是模型性能表现和模型训练时间的重要影响因素。提出了一种基于预训练VGG11模型的坏点检测方法,通过微调基于ImageNet数据集预训练的VGG11模型获得坏点检测的待训练模型。采用保留预训练模型权重、冻结卷积层的策略进行模型训练,采用ICCAD 2012数据集进行模型训练和测试。与现有方法相比,所提方法的模型综合性能表现更好,所需的模型训练时间更少。所提方法有助于提高掩模版图的坏点检测效率,缩短集成电路生产的周期。Objective Lithographic tool is an important device for largescale IC manufacturing.Its function is to transfer mask patterns into photoresists on wafers.Nowadays,the designed feature size of IC is below 10 nm,and the number of transistors of an IC is as high as tens of billions.With the demand for high integration and good performance,the physical design of IC continues to shrink,and lithographic printability has become one of the critical issues in IC design and manufacturing.Affected by the layout design and lithography process,the lithography results of some patterns in the layout are quite different from that of the target patterns,which results in shortcircuit or opencircuit problems.These problems will cause lithography hotspots.In order to reduce lithography hotspots,hotspot detection and layout correction are carried out in turn in the layout design phase.The performance of the hotspot detection affects the period and yield of IC manufacturing.Hotspot detection is one of the important techniques for IC design and manufacturing.For available hotspot detection methods,the hotspot detection method based on lithography simulation is timeconsuming,and the hotspot detection method based on pattern matching is invalid for unknown hotspot patterns.The hotspot detection method based on machine learning has good performance in speed and accuracy and has been widely studied.Transfer learning has been applied in the hotspot detection method based on machine learning and achieved positive model performance.Model performance and model training time affect the application of the hotspot detection method based on transfer learning.In this study,a lithography hotspot detection method based on a pretrained VGG11 model is proposed.The proposed method helps to improve the model performance and model training time.Methods In this study,we adopt a transfer learning strategy for model training of hotspot detection.First,the ImageNet dataset is used to pretrain the VGG11 model,and the pretrained VGG11 model is used as the model

关 键 词：测量 光刻 坏点检测 机器学习 迁移学习 

分 类 号：TN305.7[电子电信—物理电子学]