Early Power Prediction of Digital VLSI Circuits Using Machine Learning

Abstract

The need for electronic devices that are more streamlined, more durable, and more functional has grown in the dynamic environment of contemporary civilization. In order to meet these goals, more components must be integrated onto smaller semiconductor chips, which will bring in a new age of low-geometry chip design. The dynamic and static power present in Integrated Circuits (ICs) make controlling power dissipation extremely difficult, despite this paradigm shift in chip architecture. The need to maximise usefulness and battery life makes efficient power management essential. newlineThe goal of this research project is to develop a novel method for pre- and post-synthesis machine learning approaches to estimate power dissipation in Integrated Circuits (ICs). Precise power estimation throughout the design stage facilitates efficient power distribution planning by floor plan engineers and yields accurate power pad and strip consumption predictions. Main goal is to create a different approach to IC power dissipation newline