Using Heuristic Optimization to Set SRAF Rules

被引：1

作者：

Wang, ChangAn ^{[1
]}

Chen, Norman ^{[1
]}

Kallingal, Chidam ^{[1
]}

Wilkinson, William ^{[1
]}

Liu, Jian ^{[1
]}

Leslie, Alan ^{[1
]}

机构：

[1] Globalfoundries Inc, OPC Technol, Hopewell Jct, NY 12533 USA

来源：

OPTICAL MICROLITHOGRAPHY XXX | 2017年 / 10147卷

关键词：

sub-resolution assisted feature; SRAF; RBSRAF; MBSRAF; OPC; genetic algorithm; GA; heuristic optimization; PVBand and runtime;

D O I：

10.1117/12.2258233

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

A heuristic optimization approach has been developed to optimize SRAF (sub resolution assist feature) placement rules for advanced technology nodes by using a genetic algorithm. This approach has demonstrated the capability to optimize a rule-based SRAF (RBSRAF) solution for both 1D and 2D designs to improve PVBand and avoid SRAF printing. Compared with the MBSRAF based POR (process of record) solution, the optimized RBSRAF can produce a comparable PVBand distribution for a full chip test case containing both random SRAM and logic designs with a significant 65% SRAF generation time reduction and 55% total OPC time reduction.

引用

页数：10

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