System and method for esl modeling of machine learning

Abstract

A non-transitory computer-readable storage medium is encoded with a set of instructions for designing a semiconductor device using electronic system level (ESL) modeling for machine learning applications that, when executed by at least one processor, cause the at least one processor to: retrieve a source code operable to execute a plurality of operations of a machine learning algorithm; classify a first group of the plurality of operations as slow group operations and classify a second group of the plurality of operations as fast group operations, based on a time required to complete each operation; define a neural network operable to execute the slow group operations; define a trained neural network configuration including a plurality of interconnected neurons operable to execute the slow group operations; and generate an ESL platform for evaluating a design of a semiconductor device based on the trained neural network configuration.