With the down-scaling of CMOS technology, the design complexity of very large-scale integrated is increasing. Although the application of machine learning (ML) techniques in electronic design automation (EDA) can trace its history back to the 1990s, the recent breakthrough of ML and the increasing complexity of EDA tasks have aroused more interest in incorporating ML to solve EDA tasks. In this article, we present a comprehensive review of existing ML for EDA studies, organized following the EDA hierarchy.

中文翻译：

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用于电子设计自动化的机器学习：调查

随着CMOS技术的缩小，超大规模集成的设计复杂度正在增加。尽管机器学习 (ML) 技术在电子设计自动化 (EDA) 中的应用可以追溯到 1990 年代，但最近 ML 的突破和 EDA 任务的日益复杂性引起了人们对将 ML 用于解决 EDA 任务的更多兴趣。在本文中，我们对现有的用于 EDA 研究的 ML 进行了全面回顾，按照 EDA 层次结构进行组织。