图神经网络集成电路设计，可靠性和安全性：调查和工具

IF 28 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2025-09-22 DOI:10.1145/3769081

Ziad El Sayed, Zeng Wang, Hana Selmani, Johann Knechtel, Ozgur Sinanoglu, Lilas Alrahis

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引用次数: 0

摘要

图神经网络（gnn）在社交网络和生物学等许多领域具有显著的先进的学习和预测任务。考虑到集成电路（ic）固有的图形结构，GNNs在各种集成电路相关任务中也显示出强大的结果。在这里，我们回顾了集成电路的三个关键领域的GNN方法：电子设计自动化（EDA）、可靠性和硬件安全性。我们介绍了一个全面的分类和调查，涵盖了gnn的各种任务及其解决方案。我们还概述了可伸缩性和EDA工具集成等关键挑战。最后，我们提出了GNN4CIRCUITS，这是一个用于各种IC任务的即插即用GNN集成的开源工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Graph Neural Networks for Integrated Circuit Design, Reliability, and Security: Survey and Tool

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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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.