Distance metric for accurate lithographic hotspot classification using radial and angular functions

摘要

An dual function distance metric for pattern matching based hotspot clustering is described. The dual function distance metric can handle patterns containing multiple polygons, is easy to compute, and is tolerant of small variations or shifts of the shapes. Compared with an XOR distance metric pattern clustering, the dual function distance metric can achieve up to 37.5% accuracy improvement with 2×-4× computational cost in the context of cluster analysis. The dual function distance metric is reliable and accurate for characterizing clips (e.g. hotspots), thereby making it desirable for industry applications.

主权项

1. A method of characterizing a plurality of clips of an integrated circuit layout for clustering, the method comprising:
determining a total distance metric for a first clip and a second clip; and performing said determining the total distance metric for multiple transformations of the first clip to determine a minimized total distance metric for the first and second clips, each transformation being a reflection or a rotation of the first clip, wherein the minimized total distance metric determines whether the first and second clips should be clustered, wherein said determining the total distance metric includes integrating differences of radial and angular functions for polygons in the first and second clips to provide a distance metric, which is compared to a predetermined threshold to determine whether polygons in the first and second clips are a matched pair, the method being performed by a computer.