Clustering and pattern matching for an automatic hotspot classification and detection system

Justin Ghan; Ning Ma; Sandipan Mishra; Costas Spanos; Kameshwar Poolla; Norma Rodriguez; Luigi Capodieci

doi:10.1117/12.814328

12 March 2009 Clustering and pattern matching for an automatic hotspot classification and detection system

Justin Ghan, Ning Ma, Sandipan Mishra, Costas Spanos, Kameshwar Poolla, Norma Rodriguez, Luigi Capodieci

Proceedings Volume 7275, Design for Manufacturability through Design-Process Integration III; 727516 (2009) https://doi.org/10.1117/12.814328
Event: SPIE Advanced Lithography, 2009, San Jose, California, United States

Abstract

This paper provides details of the implementation of a new design hotspot classification and detection system, and presents results of using the system to detect hotspots in layouts. A large set of hotspot snippets is grouped into a small number of clusters containing geometrically similar hotspots. A fast incremental clustering algorithm is used to perform this task efficiently on very large datasets. Each cluster is analyzed to produce a characterization of a class of hotspots, and a pattern matcher is used to detect hotspots in new design layouts based on the hotspot class descriptions.

Citation Download Citation

Justin Ghan, Ning Ma, Sandipan Mishra, Costas Spanos, Kameshwar Poolla, Norma Rodriguez, and Luigi Capodieci "Clustering and pattern matching for an automatic hotspot classification and detection system", Proc. SPIE 7275, Design for Manufacturability through Design-Process Integration III, 727516 (12 March 2009); https://doi.org/10.1117/12.814328

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