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Hotspot detection based on litho-aware machine learning

机译:基于岩度感知机器学习的热点检测

摘要

Aspects of the disclosed technology relate to techniques of hotspot detection. Pinching-type hotspot candidates and bridging-type hotspot candidates are first identified in the layout design based on predetermined criteria. Simulation is then performed to derive aerial image intensity values for a plurality of sites on each of the pinching-type and bridging-type hotspot candidates. Pinching-type hotspots are determined from the pinching-type hotspot candidates based on one or more machine learning models for pinching-type hotspots, and bridging-type hotspots are determined from the bridging-type hotspot candidates based on one or more machine learning models for bridging-type hotspots. The input vector for the machine learning models is the aerial image intensity values for the plurality of sites.
机译:所公开的技术的各方面涉及热点检测技术。 首先基于预定标准在布局设计中首先在布局设计中识别捏型热点候选者和桥接型热点候选。 然后执行模拟以导出在每个捏合类型和桥接型热点候选中的多个站点的空中图像强度值。 捏合型热点是根据一个或多个机器学习模型确定用于捏型热点的机器学习模型,并且桥接型热点根据一个或多个机器学习模型从桥接型热点候选中确定 桥接式热点。 机器学习模型的输入向量是多个站点的空中图像强度值。

著录项

  • 公开/公告号US11113445B2

    专利类型

  • 公开/公告日2021-09-07

    原文格式PDF

  • 申请/专利权人 MENTOR GRAPHICS CORPORATION;

    申请/专利号US201816135236

  • 发明设计人 JEA WOO PARK;JUAN ANDRES TORRES ROBLES;

    申请日2018-09-19

  • 分类号G06F30/398;G06F30/18;G03F7/20;G06N20;G06F30/20;G06N20/10;

  • 国家 US

  • 入库时间 2022-08-24 20:52:21

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