A Survey of the Different Intelligent Algorithms for the VLSI-Based Design Flows for Various Embedded Applications in Electronics Engineering

https://doi.org/10.46610/JOESP.2022.v07i03.003

Abstract

The AI/ML applications and techniques that could be applied in VLSI design technology are briefly reviewed in this study. The integrated circuit (IC) industry will undoubtedly face challenges in the nano-meter regime related to the research and development of methods that could reduce design complexity brought on by increasing process variability and reducing the turnaround time of chip manufacture. The majority of the traditional methods utilized for these tasks involve manual labor, which requires time and resources. Contrarily, the unique learning strategies of artificial intelligence enable the design and testing of very large-scale integration (VLSI) to benefit from several innovative automated ways (AI). Artificial intelligence (AI) and machine learning (ML) algorithms use automated learning algorithms to reduce the time and effort needed to interpret and process data within and across different abstraction levels, enhancing IC yield and accelerating manufacturing turnaround. This article examines the formerly employed automated AI/ML methods for VLSI design and manufacture. The project that is the subject of this paper is a P.G. (M.Tech) student's technical seminar report, which is a component of the seminar that each student must deliver on any topic during the second semester of the PG program.