{"title":"Post-placement lithographic hotspot detection and removal in one-dimensional gridded designs","authors":"Jen-Yi Wuu, Mark Simmons, M. Marek-Sadowska","doi":"10.1109/ISQED.2012.6187494","DOIUrl":null,"url":null,"abstract":"As double patterning techniques mature, they become the primary approaches enabling feature size scaling beyond 32nm. Although it is possible to print dense patterns by splitting the design into two masks, printability problems and pattern distortion remains a major concern. In this paper, we study the potential lithographic hotspots that may occur between the line ends in one-dimensional gridded designs obtained with Line-End Cut (LEC) method [2]. We propose a post-placement hotspot detection and removal algorithm that perturbs the cell locations to eliminate all hotspots. Hotspot detection is performed using a pattern classifier based on machine learning techniques. Experimental results show that we can successfully eliminate all hotspots with excellent runtime efficiency and insignificant overhead on estimated wire lengths.","PeriodicalId":205874,"journal":{"name":"Thirteenth International Symposium on Quality Electronic Design (ISQED)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Thirteenth International Symposium on Quality Electronic Design (ISQED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISQED.2012.6187494","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
As double patterning techniques mature, they become the primary approaches enabling feature size scaling beyond 32nm. Although it is possible to print dense patterns by splitting the design into two masks, printability problems and pattern distortion remains a major concern. In this paper, we study the potential lithographic hotspots that may occur between the line ends in one-dimensional gridded designs obtained with Line-End Cut (LEC) method [2]. We propose a post-placement hotspot detection and removal algorithm that perturbs the cell locations to eliminate all hotspots. Hotspot detection is performed using a pattern classifier based on machine learning techniques. Experimental results show that we can successfully eliminate all hotspots with excellent runtime efficiency and insignificant overhead on estimated wire lengths.
随着双模式技术的成熟,它们成为实现超过32nm特征尺寸扩展的主要方法。虽然可以通过将设计分成两个掩模来打印密集的图案,但可打印性问题和图案失真仍然是一个主要问题。在本文中,我们研究了用线端切割(line - end Cut, LEC)方法获得的一维网格设计中线端之间可能出现的光刻热点[2]。我们提出了一种放置后热点检测和去除算法,该算法通过扰动单元位置来消除所有热点。热点检测使用基于机器学习技术的模式分类器执行。实验结果表明,该方法能够成功地消除所有热点,并且具有良好的运行效率和较小的估计线长开销。