Invariant property-based clustering of circuit images for electronic design automation (EDA) applications

A system comprising:

• an image clustering engine configured to:
• access a set of circuit images;
• cluster the circuit images into different groups via an unsupervised learning process, wherein clustering by the unsupervised learning process is invariant to each invariant property of an invariant property set, and wherein:
• a given invariant property in the invariant property set corresponds to a given image transformation;
• the invariant properties in the invariant property set are discrete;
• and
• a total number of invariant properties in the invariant property set is finite;
• and
• a cluster provision engine configured to provide the clustered circuit images for further processing or analysis by an electronic design automation (EDA) application.

A non-transitory machine-readable medium comprising instructions that, when executed by a processor, cause a computing system to:

• access a set of circuit images;
• cluster the circuit images into different groups via an unsupervised learning process, wherein clustering by the unsupervised learning process is invariant to each invariant property of an invariant property set, and wherein:
• a given invariant property in the invariant property set corresponds to a given image transformation;
• the invariant properties in the invariant property set are discrete;
• and
• a total number of invariant properties in the invariant property set is finite;
• and
• provide the clustered circuit images for further processing or analysis by an electronic design automation (EDA) application.