3 citations · 6 across the 4 of their papers we have counts for
4 papers
BitGNN: Unleashing the Performance Potential of Binary Graph Neural Networks on GPUs
Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen +2
Recent studies have shown that Binary Graph Neural Networks (GNNs) are promising for saving computations of GNNs through binarized tensors. Prior work, however, mainly focused on a…
Survey: Exploiting Data Redundancy for Optimization of Deep Learning
Jou-An Chen, Wei Niu, Bin Ren +2
Data redundancy is ubiquitous in the inputs and intermediate results of Deep Neural Networks (DNN). It offers many significant opportunities for improving DNN performance and effic…
Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU
Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen +3
In a general graph data structure like an adjacency matrix, when edges are homogeneous, the connectivity of two nodes can be sufficiently represented using a single bit. This insig…
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
Wei Niu, Mengshu Sun, Zhengang Li +7
Mobile devices are becoming an important carrier for deep learning tasks, as they are being equipped with powerful, high-end mobile CPUs and GPUs. However, it is still a challengin…