Survey reviews GNN methodologies for electronic design automation and hardware security, highlighting challenges.
Graph neural networks (GNNs) have significantly advanced learning and predictive tasks in many domains like social networks and biology. Given the inherent graph structure of integrated circuits (ICs), GNNs have also shown strong results for various IC-related tasks. Here, we review GNN methodologies across three key areas for ICs: electronic design automation (EDA), reliability, and hardware security. We introduce a comprehensive taxonomy and survey, covering various tasks and their solutions by GNNs in depth. We also outline key challenges like scalability and EDA tool integration. Finally, we present GNN4CIRCUITS, an open-source tool for plug-and-play GNN integration for various IC tasks.
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Sayed et al. (2025) studied this question.
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