Role Of Machine Learning In Vlsi Ic Design

Abstract

AI has influenced the field of integrated circuits, this being its first application in AI. This technology replaces the traditional VLSI design methodology existing today. Automation of design devel- opments have been implemented by replacing the time consuming manual design’s generated by humans. This advancement would lead to massive revolution in the area of hardware computation and AI research domain. With the advent of modern chip, which are highly complex, it is a very tedious and slow process to design with humanly aids. The process of confirming the critical design’s manually also finds no hope. Hence automation of various task is done in past 40 years, and many other complex task are automated. When someone comes with a new idea (in view with computation, processing, optimization, interconnect fabrication) the process of designing is automated. Companies such as IBM and Intel are enabled with their own CAD Organization for handling these automated tasks. CAD tools have been sold by many companies such as Candence, Synopsis and Mentor Graphics serves as implementation of AI in Chip design. Machine learning has extended its arm in aiding feasible solution for many kinds of problems in many engineering fields. The role of machine learning in EDA tools business, have expanded its potential in reducing the time consumption in design implementation, cost reduction, productivity of design products. In this paper we have reviewed the role machine learning in VLSI chip design and implemented ML based BIST.