Layout features become highly susceptible to lithography process fluctuations due to the widening subwavelengthlithography gap. Problematic layout patterns incur poor printability even if they pass design rule checking. These hotspotsshould be detected and removed at early design phases to improve manufacturability. While existing studies mainly focuson hotspot detection and pattern classification, hotspot pattern library generation is rarely addressed in literature but crucialto the effectiveness and efficiency of hotspot detection. For an advanced process, in addition to yield-limiting patternsinherent from old processes and computation intensive lithography simulation, defect silicon images (SEM images)inspected from test wafers provide more realistic process-dependent hotspots. For facilitating hotspot pattern librarygeneration, we raise a pattern matching problem of searching design layout patterns that may induce problematic SEMimages. The key challenge is the various shape distortions between an SEM image and corresponding design layouts.Directly matching either feature points or shapes of both is thus not applicable. We observe that even with shape distortions,matched design layouts and the SEM image have similar density distribution. Therefore, in this paper, we propose anefficient multilevel pixilation framework to seek layout clips with similar density distribution from coarse- to finegranularitiesto an SEM image. The proposed framework possesses high parallelism. Our results show that the proposedmethod can effectively and efficiently identify matched layout pattern candidates.
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