Using heuristic optimization to set SRAF rules

ChangAn Wang; Norman Chen; Chidam Kallingal; William Wilkinson; Jian Liu; Alan Leslie

doi:10.1117/12.2258233

24 March 2017 Using heuristic optimization to set SRAF rules

ChangAn Wang, Norman Chen, Chidam Kallingal, William Wilkinson, Jian Liu, Alan Leslie

Proceedings Volume 10147, Optical Microlithography XXX; 1014706 (2017) https://doi.org/10.1117/12.2258233
Event: SPIE Advanced Lithography, 2017, San Jose, California, United States

Abstract

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.

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Citation Download Citation

ChangAn Wang, Norman Chen, Chidam Kallingal, William Wilkinson, Jian Liu, and Alan Leslie "Using heuristic optimization to set SRAF rules", Proc. SPIE 10147, Optical Microlithography XXX, 1014706 (24 March 2017); https://doi.org/10.1117/12.2258233

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