Introduction to the Special Issue on Machine Learning for CAD/EDA

Abstract

Recent advances in machine learning (ML) have brought revolutions for a variety of applications like computer vision, recommendation systems, and robotics. Many researches have been exploring the applications of ML to CAD/EDA problems. However, the design processes in the CAD flow present challenges to achieve high accuracy, generality, and efficiency. Compared to traditional ML applications such as computer vision, parallel advances in ML and CAD are often required to achieve effectiveness in the design processes. This special issue on Machine Learning for CAD/EDA focuses on concepts and methods for applying machine learning techniques to improve design performance and speed up design closure in the CAD flow.