Method of predicting characteristics of semiconductor device and computing device performing the same

A method of predicting characteristics of a semiconductor device in a target semiconductor product, the method being performed by at least one processor executing program codes, the program codes stored in computer readable media, the method comprising:

• generating basic training data corresponding to a combination of process data, device data and simulation result data using a plurality of compact models, each of the plurality of compact models generating 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, the plurality of compact models respectively corresponding to a plurality of process data and a plurality of semiconductor products;
• training a deep learning model based on the basic training data such that the deep learning model is configured to output prediction data and uncertainty value, the prediction data indicating the characteristics of the semiconductor device and the uncertainty value indicating uncertainty of the prediction data;
• retraining the deep learning model based on the uncertainty data;
• and
• generating target prediction data based on the deep learning model, the device data, and the process data corresponding to the target semiconductor product such that the target prediction data indicates characteristics of the semiconductor device included in a target semiconductor product included in the target semiconductor product.

A computing device comprising:

• a computer readable medium storing program codes and a plurality of compact models, the program codes being executed by the at least one processor to generate a deep learning model using the plurality of compact models, each of the plurality of compact models generating simulation result data by performing a simulation based on the device data, the simulation result data indicating characteristics of semiconductor devices corresponding to the device data, the plurality of compact models respectively corresponding to a plurality of process data. and a plurality of semiconductor products;
• and
• at least one processor, the at least one processor, when executing the program codes, configured to
• generate basic training data corresponding to a combination of process data, device data and simulation result data using the plurality of compact models,
• train the deep learning model based on the basic training data such that the deep learning model is configured to output prediction data;
• and
• generate target prediction data based on the deep learning model, the device data and the process data corresponding to the target semiconductor product such that the target prediction data indicates characteristics of the semiconductor device included in the target semiconductor product.