Jen-Yi Wuu, F. Pikus, A. Torres, M. Marek-Sadowska
{"title":"Rapid layout pattern classification","authors":"Jen-Yi Wuu, F. Pikus, A. Torres, M. Marek-Sadowska","doi":"10.1109/ASPDAC.2011.5722295","DOIUrl":null,"url":null,"abstract":"Printability of layout objects becomes increasingly dependent on neighboring shapes within a larger and larger context window. In this paper, we propose a two-level hotspot pattern classification methodology that examines both central and peripheral patterns. Accuracy and runtime enhancement techniques are proposed, making our detection methodology robust and efficient as a fast physical verification tool that can be applied during early design stages to large-scale designs. We position our method as an approximate detection solution, similar to pattern matching-based tools widely adopted by the industry. In addition, our analyses of classification results reveal that the majority of non-hotspots falsely predicted as hotspots have printed CD barely over the minimum allowable CD threshold. Our method is verified on several 45 nm and 32 nm industrial designs.","PeriodicalId":316253,"journal":{"name":"16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"60","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPDAC.2011.5722295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 60
Abstract
Printability of layout objects becomes increasingly dependent on neighboring shapes within a larger and larger context window. In this paper, we propose a two-level hotspot pattern classification methodology that examines both central and peripheral patterns. Accuracy and runtime enhancement techniques are proposed, making our detection methodology robust and efficient as a fast physical verification tool that can be applied during early design stages to large-scale designs. We position our method as an approximate detection solution, similar to pattern matching-based tools widely adopted by the industry. In addition, our analyses of classification results reveal that the majority of non-hotspots falsely predicted as hotspots have printed CD barely over the minimum allowable CD threshold. Our method is verified on several 45 nm and 32 nm industrial designs.