通过布局片段聚类进行系统缺陷识别

W. Tam, O. Poku, Shawn Blanton
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引用次数: 40

摘要

在纳米级集成电路技术中,由设计过程相互作用引起的系统缺陷是造成成品率损失的主要因素。测试结构在特征多样性和特征体积方面不能充分地表示产品,因此不能识别影响产品的所有系统缺陷。本文描述了一种使用诊断来识别不产生预期结果的布局特征的方法。具体来说,聚类技术被应用于从(理想情况下)统计上显著数量的IC故障中找出诊断相关区域的布局片段,以识别特征共性。涉及工业芯片的实验证明了由于光刻热点可能导致的系统良率损失的识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic defect identification through layout snippet clustering
Systematic defects due to design-process interactions are a dominant component of integrated circuit (IC) yield loss in nano-scaled technologies. Test structures do not adequately represent the product in terms of feature diversity and feature volume, and therefore are unable to identify all the systematic defects that affect the product. This paper describes a method that uses diagnosis to identify layout features that do not yield as expected. Specifically, clustering techniques are applied to layout snippets of diagnosis-implicated regions from (ideally) a statistically-significant number of IC failures for identifying feature commonalties. Experiments involving an industrial chip demonstrate the identification of possible systematic yield loss due to lithographic hotspots.
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