Synopsys, Inc.
CLASSIFICATION OF PATTERNS IN AN ELECTRONIC CIRCUIT LAYOUT USING MACHINE LEARNING BASED ENCODING

Abstract:

A system performs distributed or parallel pattern extraction and clustering for pattern classification of large layouts of electronic circuits. The system identifies circuit patterns with a layout representation. The system encodes the circuit patterns using a neural network based autoencoder to generate encoded circuit patterns that can be stored efficiently. The system clusters the encoded circuit patterns into an arbitrary number of clusters based upon a high degree of similarity. The clusters of circuit patterns may be used for training and evaluation of machine learning based models.