Method and computing device for generating neural network model and performing circuit simulation by using the neural network model

A computing device comprising at least one processor and a memory,

• wherein the memory stores instructions that, when executed by the at least one processor, allow the at least one processor to generate a neural network model and perform a circuit simulation by using the neural network model, and
• the at least one processor is configured to:
• generate sample data by performing a process simulation based on a temperature and a process parameter;
• train the neural network model based on the sample data;
• perform a lightweight operation on the neural network model to generate a lightweight neural network model;
• re-train a lightweight neural network model;
• and
• perform the circuit simulation with the process parameter as an input by using the re-trained lightweight neural network model.

A method of generating a neural network model and performing a circuit simulation by using the neural network model, the method comprising:

• generating sample data by performing a process simulation based on a temperature and a process parameter;
• dividing the sample data into training data and validation data;
• training the neural network model based on the training data;
• determining whether a fit between target data and output data of the neural network model is accurate;
• adjusting a parameter of the neural network model until a threshold fit between the target data and the output data is reached;
• performing a lightweight operation on the neural network model to generate a lightweight neural network model;
• re-training the lightweight neural network model based on the validation data;
• converting the lightweight neural network model into a format corresponding to a circuit simulator;
• and
• performing the circuit simulation with the process parameter as an input by using the converted lightweight neural network model