Method of generating deep learning model and computing device performing the same

A method of generating a deep learning model, the method being performed by executing program codes by at least one processor, the program codes being stored in computer readable media, the method comprising:

• generating basic training data corresponding to a combination of device data and simulation result data using a compact model, the compact model configured to generate the simulation result data by performing a simulation based on the device data, the simulation result data indicating characteristics of a semiconductor device corresponding to the device data;
• training the deep learning model based on the basic training data such that the deep learning model is configured to output prediction data, a model uncertainty value, and a data uncertainty value, the prediction data indicating the characteristics of the semiconductor device, the model uncertainty value indicating the uncertainty of the prediction data caused by insufficiency of the basic training data, and the data uncertainty value indicating the uncertainty of the prediction data caused by noises of the basic training data;
• performing a first retraining such that the deep learning model that has been trained based on the basic training data is further trained based on the model uncertainty value;
• and
• performing a second retraining such that the deep learning model that has been trained based on the basic training data is initialized, and the initialized deep learning model is trained based on the data uncertainty value.

A computing device comprising:

• at least one processor;
• and
• a computer readable medium storing program codes and a compact model, the program codes being executed by the at least one processor to generate a deep learning model, the compact model generating simulation result data indicating characteristics of a semiconductor device corresponding to device data by performing simulation based on the device data,
• the at least one processor executing the program codes to:
• generate basic training data corresponding to a combination of the device data and the simulation result data using the compact model;
• train the deep learning model based on the basic training data such that the deep learning model is configured to output prediction data and uncertainty data, the prediction data indicating the characteristics of the semiconductor device and the uncertainty data indicating uncertainty of the prediction data;
• and
• retrain the deep learning model based on the uncertainty data.