DETECTING HOTSPOTS USING MACHINE LEARNING ON DIFFRACTION PATTERNS

摘要

A mechanism is provided in a data processing system for detecting lithographic hotspots. The mechanism receives a design layout. The mechanism generates spatial pattern clips from the design layout. The mechanism performs a transform on the spatial pattern clips to form frequency domain pattern clips. The mechanism performs feature extraction on the frequency domain pattern clips to form frequency domain features. The mechanism utilizes the extracted features on a set of training samples to train a machine learning classifier model. The mechanism classifies a set of previously unseen patterns, based on frequency domain features of the previously unseen patterns using the trained machine learning classifier model, into hotspots and non-hotspots.

主权项

1. A method, in a data processing system, for detecting lithographic hotspots, the method comprising:
receiving a design layout; generating spatial pattern clips from the design layout; performing a transform on the spatial pattern clips to form frequency domain pattern clips; performing feature extraction on the frequency domain pattern clips to form frequency domain features; utilizing the extracted features on a set of training samples to train a machine learning classifier model; and classifying a set of previously unseen patterns, based on frequency domain features of the previously unseen patterns using the trained machine learning classifier model, into hotspots and non-hotspots.