Classification and localization of hotspots in integrated physical design layouts

A method for fabricating an integrated circuit, comprising:

• training a convolutional neural network using a training set that includes known multi-layer physical design layout patterns that are classified according to whether the patterns include a hotspot;
• determining whether an input multi-layer physical design layout pattern includes a hotspot using the convolutional neural network on all layers of the multi-layer circuit physical layout patterns simultaneously;
• verifying that the input physical design layout pattern includes a hotspot using a simulation after determining that the input physical design layout pattern includes a hotspot using the convolutional neural network;
• generating a hotspot heat map for the input multi-layer physical design layout pattern that shows regions with a higher likelihood of a hotspot as a higher heat map intensity;
• adjusting the input physical design pattern to cure the hotspot;
• and
• fabricating a circuit in accordance with the adjusted input multi-layer physical design layout pattern.

A system for fabricating an integrated circuit, comprising:

• a training module configured to train a machine learning model using a training set that includes known physical design layout patterns that are classified according to whether the patterns include a hotspot, wherein the machine learning model is configured to determine whether an input physical design layout pattern includes a hotspot using the machine learning model and to generate a hotspot localization for the input physical design layout pattern;
• a layout adjustment module configured to adjust the input physical design pattern to cure the hotspot;
• and
• a fabrication module configured to trigger fabrication of a circuit in accordance with the adjusted input physical design layout pattern.