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首页> 外文期刊>Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on >An Automatic Optical Simulation-Based Lithography Hotspot Fix Flow for Post-Route Optimization
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An Automatic Optical Simulation-Based Lithography Hotspot Fix Flow for Post-Route Optimization

机译:基于自动光学模拟的光刻热点修复流程,用于路线后优化

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In this paper, an optical simulation-based lithography hotspot fix guidance generator and an automatic hotspot fix flow are proposed. We develop our aerial image simulation engine by enhancing the traditional sum of coherence system method. Subject to the shape changes, a strong correlation between the aerial image intensity difference maps of pre-optical proximity correction (OPC) and post-OPC schemes is found. We collect near a litho hotspot in a pre-OPC layout some fix actions that are local shape changes to optimize the optical intensity. Then, fix guidances will be selected from the collected fix actions by a heuristic algorithm and input to a router for fixing the hotspot. We integrate the fix guidance generation method with a commercial lithography hotspot detection tool to create an automatic post-route optical-simulation-embedded local fix (OSELF) flow and test with industry 65 nm designs. Compared with the commercial flow that uses only local fix, our method has a $1.4times hbox{--}1.9times$ fix rate, similar run time, no new design rule check violation, and negligible circuit timing impacts. We also combine our OSELF algorithm with a rip-up and reroute engine, and test on the same designs. Compared to the commercial tool that uses a hybrid (local fix plus reroute) fix flow, our combined flow runs $1.7times hbox{--}2.9times$ faster with 45–55% circuit timing impact. Both flows achieve a 100% hotspot fix rate.
机译:本文提出了一种基于光学仿真的光刻热点修复指导生成器和自动热点修复流程。我们通过增强传统相干系统方法的总和来开发航空图像仿真引擎。受到形状变化的影响,发现在光学前校正(OPC)和后OPC方案的航空图像强度差异图之间存在很强的相关性。我们在OPC之前的版图中的一个光刻热点附近收集一些固定动作,这些动作是局部形状变化以优化光强度。然后,将通过启发式算法从收集的修复操作中选择修复指南,并将其输入到路由器中以修复热点。我们将修复指导生成方法与商业光刻热点检测工具集成在一起,以创建自动的路由后光学模拟嵌入式本地修复(OSELF)流程,并使用65 nm工业设计进行测试。与仅使用本地修复的商业流程相比,我们的方法具有1.4倍的hbox {-} 1.9倍的修复率,相似的运行时间,没有违反新的设计规则检查以及可忽略的电路时序影响。我们还将OSELF算法与翻录和重新路由引擎相结合,并在相同的设计上进行测试。与使用混合(本地修复和重新路由)修复流的商用工具相比,我们的组合流运行时的速度是hbox {-}的1.7倍,是2.9倍,而电路时序影响为45-55%。两种流程均达到了100%的热点修复率。

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