Abstract
The increasing complexity and size of design space poses significant challenges for integrated circuit (IC) design. This article discusses the potential of machine learning (ML) methods to address these challenges and provides a comprehensive survey of the current state of knowledge along both IC design problems and ML-based solutions. The article also summarizes the open problems at the intersection of advanced IC design and ML.
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