Abstract: Methods, apparatus, systems, and articles of manufacture to predict outputs of electronic design automation (EDA) tools using machine learning are disclosed. An example apparatus includes memory; machine readable instructions; and programmable circuitry to at least one of instantiate or execute the machine readable instructions to: access circuit design data to be optimized by an EDA tool as part of a circuit design process for an integrated circuit; extract features from the circuit design data; apply a machine learning model to the features to estimate an output of the EDA tool, the estimated output determined without execution of the EDA tool; and provide results of the estimated output.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for methods and apparatus to generate I/O timing constraint predictions for system-on-chips using machine learning. An apparatus is disclosed herein comprising at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to extract delay features from a first system-on-chip design and a second system-on-chip design, apply a machine learning model to the extracted delay features to determine an estimated delay for the first system-on-chip design, compare the estimated delay for the first system-on-chip design to the second system-on-chip design to determine an error of the first system-on-chip design, and update the second system-on-chip design based on the error determined for the first system-on-chip design.