Machine learning-based down selection of candidate hotspot locations of circuit designs

Abstract

A method may include the steps of accessing an input data set of hotspot locations on manufactured circuits of a circuit design. The hotspot locations may be confirmed through a high precision imaging process from a set of candidate locations of the circuit design determined by a low precision imaging process. The method may further include correlating the hotspot locations to layout data for the circuit design, extracting fragment feature vectors for the hotspot locations from optical proximity correction (OPC) fragments of the layout data, processing the fragment feature vectors, providing the processed fragment feature vectors as a training set for training a machine-learning model, and applying the machine-learning model to down select a different set of candidate locations determined by the low precision imaging process.