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Automatic hotspot classification using pattern-based clustering

Authors :
Luigi Capodieci
Sandipan Mishra
Ning Ma
Costas J. Spanos
Justin Ghan
Kameshwar Poolla
Norma Rodriguez
Source :
SPIE Proceedings.
Publication Year :
2008
Publisher :
SPIE, 2008.

Abstract

This paper proposes a new design check system that works in three steps. First, hotspots such as pinching/bridging are recognized in a product layout based on thorough process simulations. Small layout snippets centered on hotspots are clipped from the layout and similarities between these snippets are calculated by computing their overlapping areas. This is accomplished using an efficient, rectangle-based algorithm. The snippet overlapping areas can be weighted by a function derived from the optical parameters of the lithography process. Second, these hotspots are clustered using a hierarchical clustering algorithm. Finally, each cluster is analyzed in order to identify the common cause of failure for all the hotspots in that cluster, and its representative pattern is fed to a pattern-matching tool for detecting similar hotspots in new design layouts. Thus, the long list of hotspots is reduced to a small number of meaningful clusters and a library of characterized hotspot types is produced. This could lead to automated hotspot corrections that exploit the similarities of hotspots occupying the same cluster. Such an application will be the subject of a future publication.

Details

ISSN :
0277786X
Database :
OpenAIRE
Journal :
SPIE Proceedings
Accession number :
edsair.doi...........d31a3765afb83e772046860183bf1149
Full Text :
https://doi.org/10.1117/12.772867