Cell-level analysis method of memory based on graph neural network and computing device for performing the same

A computing device comprising:

• one or more processors;
• a memory;
• and
• one or more programs,
• wherein the one or more programs are configured to be stored in the memory and executed by the one or more processors, and
• the one or more programs include:
• instructions for acquiring information on a location of each cell in the memory;
• instructions for generating graph-structured data for a target cell based on the location of each cell in the memory;
• and
• instructions for training a graph neural network model to predict one or more of an electrical characteristic of the target cell and a program and verify level (PV level) of the target cell by inputting the graph-structured data into the graph neural network model.

A computer program stored in a non-transitory computer readable storage medium, comprising one or more instructions that, when executed by a computing device having one or more processors, cause the computing device to perform operations of:

• acquiring information on a location of each cell in the memory;
• generating graph-structured data for a target cell based on the location of each cell in the memory;
• and
• training a graph neural network model to predict one or more of an electrical characteristic of the target cell and a program and verify level (PV level) of the target cell by inputting the graph-structured data into the graph neural network model.