Machine Learning in Advanced IC Design: A Methodological Survey
Tinghuan Chen, Grace Li Zhang, Bei Yu, Bing Li, Ulf Schlichtmann
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.
Topics & Concepts
Intersection (aeronautics)Computer scienceDesign methodsSurvey researchComputer architectureSystems engineeringMachine learningArtificial intelligenceEngineeringPsychologyTransport engineeringMechanical engineeringApplied psychologyAdvancements in Semiconductor Devices and Circuit DesignVLSI and Analog Circuit TestingVLSI and FPGA Design Techniques