7 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
GNNear: Accelerating Full-Batch Training of Graph Neural Networks with Near-Memory Processing
Zhe Zhou, Cong Li, Xuechao Wei +2
Recently, Graph Neural Networks (GNNs) have become state-of-the-art algorithms for analyzing non-euclidean graph data. However, to realize efficient GNN training is challenging, es…
Energon: Towards Efficient Acceleration of Transformers Using Dynamic Sparse Attention
Zhe Zhou, Junlin Liu, Zhenyu Gu +1
In recent years, transformer models have revolutionized Natural Language Processing (NLP) and shown promising performance on Computer Vision (CV) tasks. Despite their effectiveness…
METRO: A Software-Hardware Co-Design of Interconnections for Spatial DNN Accelerators
Zhao Wang, Jingchen Zhu, Zhe Zhou +1
Tiled spatial architectures have proved to be an effective solution to build large-scale DNN accelerators. In particular, interconnections between tiles are critical for high perfo…
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…