A Thorough Investigation into Challenges, Advancements, and Future Directions of Machine Learning Techniques and Their Applications in VLSI Design

Abstract

The manufacture of high-performance chips has become more difficult due to the increasing complexity of VLSI circuits brought on by the need for smaller sizes and higher performance. To solve these problems, recent research investigates how Artificial Intelligence (AI) and Machine Learning (ML) can be combined with Electrical Design Automation (EDA) and VLSI Computer-Aided Design (CAD). Incorporating machine learning approaches into EDA tools is transforming VLSI design through increased accuracy, efficiency, and decreased runtime.

These developments are crucial and critical to managing the complexity of contemporary change. Technological advances in machine learning are increasingly vital to handling design problems and streamlining chip development procedures. This article examines current Machine Learning (ML) applications in VLSI CAD/EDA and emphasizes how they improve chip design and development. Designers can satisfy the growing expectations of the modern technology landscape by utilizing ML to produce more effective and high-performing chips.