Role of Machine Learning Applications in VLSI Design
Mohd Javed Khan, Pooja Gaur, Indrasen Singh, Saif Ahmad · 2025
The exploration and development of methods to lower design complexity resulting from increasing process variability and shortened chip production turnaround times is clearly an issue faced by the integrated circuit (IC) industry. The traditional methods used for these kinds of jobs are mostly costly, time-consuming, and resource-intensive. Conversely, the distinct learning strategies of machine learning offer a variety of fascinating automated methods for managing intricate and data-rich jobs in very-large-scale integration (VLSI) testing and design. This chapter provides an extensive overview of the use of machine learning techniques in VLSI design, with a focus on areas like defect detection, area reduction, performance enhancement, and power optimization. A comprehensive understanding of the present situation and possible advancements in this quickly changing junction of machine learning and VLSI design is offered by case studies and future trends.