AI RESEARCH
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware
arXiv CS.LG
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ArXi:2306.14052v2 Announce Type: replace Graph neural networks (GNNs) are emerging for machine learning research on graph-structured data. GNNs achieve state-of-the-art performance on many tasks, but they face scalability challenges when it comes to real-world applications that have numerous data and strict latency requirements. Many studies have been conducted on how to accelerate GNNs in an effort to address these challenges. These acceleration techniques touch on various aspects of the GNN pipeline, from smart.