An efficient segmented quantization for graph neural networks

Graph Neural Networks (GNNs) are recently developed machine learning approaches that exploit the advances in Neural Networks for a wide range of graph applications. While GNNs achieve promising inference accuracy improvements over conventional approaches, their efficiency suffers from expensive comp...

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Veröffentlicht in:	CCF transactions on high performance computing (Online) 2022-12, Vol.4 (4), p.461-473
Hauptverfasser:	Dai, Yue, Tang, Xulong, Zhang, Youtao
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Approximation Complexity Computer Hardware Computer memory Computer Science Computer Systems Organization and Communication Networks Efficiency Graph neural networks Inference Machine learning Mathematical analysis Neural networks Regular Paper Segments
Online-Zugang:	Volltext
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