A comparative analysis of traditional and AI-based routing algorithms in electronic design automation

Abstract

Rapid advances in artificial intelligence (AI) and machine learning have had a significant impact on various fields, including electronic design automation (EDA). This study aims to compare current EDA routing algorithms with AI-based routing algorithms, highlighting their respective advantages and limitations. Through a comprehensive analysis of existing EDA routing algorithms and artificial intelligence-based technologies, this study explores the applicability of these algorithms in different EDA scenarios, with a focus on their effectiveness and efficiency in routing tasks, and aims to compare and contrast traditional and AI-based routing algorithms in the context of electronic design automation. It also shows that the current AI technology will play an important role in the future development of EDA software. Therefore, the combination of AI technology may be the focus of EDA software development, so as to help elucidate the evolving landscape of EDA and provide insights into the potential future direction, and provide a a comprehensive understanding of their underlying methodologies, advantages, and limitations of traditional and AI-based algorithms in the context of electronic design automation.