Method and apparatus for analyzing neural network performance

A server comprising:

• a memory storing at least one instruction;
• and
• at least one processor configured to execute the at least one instruction to:
• obtain one or more of a first hardware arrangement or a first neural network model, the first hardware arrangement comprising a first plurality of interconnected components or devices, the first neural network model comprising a first plurality of operations;
• obtain a first graphical model comprising a first plurality of nodes corresponding to the obtained first hardware arrangement or the obtained first neural network model, wherein each node of the first plurality of nodes corresponds to a respective component or device of the first plurality of interconnected components or devices or a respective operation of the first plurality of operations;
• extract, based on the first graphical model, a first graphical representation of the obtained first hardware arrangement or the obtained first neural network model;
• predict, based on the first graphical representation, performance of the obtained first hardware arrangement or the obtained first neural network model;
• and
• output the predicted performance.

A method of searching for a model based on performance comprising:

• obtaining a plurality of candidate models comprising a first candidate model;
• determining whether the first candidate model satisfies a predetermined constraint;
• based on the first candidate model satisfying the predetermined constraint, profile the first candidate model to obtain ground truth values for the first candidate model;
• obtain a performance of the first candidate model based on the ground truth values for the first candidate model;
• compare the performance of the first candidate model to a performance of a current best model;
• and
• based on the performance of the first candidate model being higher than the current best model, update the current best model to be the first candidate model.