BlockGNN: Towards Efficient GNN Acceleration Using Block-Circulant Weight Matrices

Zhe Zhou, Bizhao Shi, Zhe Zhang +3

In recent years, Graph Neural Networks (GNNs) appear to be state-of-the-art algorithms for analyzing non-euclidean graph data. By applying deep-learning to extract high-level repre…