Graph Neural Networks

Graph neural networks (GNNs) have pushed the state-of-the-art (SOTA) for performance in learning and predicting on large-scale data present in social networks, biology, etc. Since integrated circuits (ICs) can naturally be represented as graphs, there has been a tremendous surge in employing GNNs for machine learning (ML)-based methods for various aspects of IC design. Given this trajectory, there is a timely need to review and discuss some powerful and versatile GNN approaches for advancing IC design.