Lithography hotspot candidate detection using coherence map

Tetsuaki Matsunawa; Taiki Kimura; Shigeki Nojima

doi:10.1117/12.2515664

20 March 2019 Lithography hotspot candidate detection using coherence map

Tetsuaki Matsunawa, Taiki Kimura, Shigeki Nojima

Proceedings Volume 10962, Design-Process-Technology Co-optimization for Manufacturability XIII; 109620Q (2019) https://doi.org/10.1117/12.2515664
Event: SPIE Advanced Lithography, 2019, San Jose, California, United States

Abstract

Lithography hotspot detection and correction in the layout design phase is important to suppress manufacturing yield loss. Although machine learning based hotspot detection methods are considered as effective solutions over conventional lithography simulation, it is still difficult to apply them to practical layout design tasks because of a trade-off between detection accuracy and false alarms. In this paper, we propose a fast, accurate and reliable method to detect lithography hotspot candidates based on coherence map. Experimental results show that our method outperforms typical machine learning based hotspot detection models on industrial benchmark.

Citation Download Citation

Tetsuaki Matsunawa, Taiki Kimura, and Shigeki Nojima "Lithography hotspot candidate detection using coherence map", Proc. SPIE 10962, Design-Process-Technology Co-optimization for Manufacturability XIII, 109620Q (20 March 2019); https://doi.org/10.1117/12.2515664

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