2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.DC2022
Characterizing and Understanding Distributed GNN Training on GPUs
Haiyang Lin, Mingyu Yan, Xiaocheng Yang +4
Graph neural network (GNN) has been demonstrated to be a powerful model in many domains for its effectiveness in learning over graphs. To scale GNN training for large graphs, a wid…
cs.AR2021★ 2 cited
RISC-NN: Use RISC, NOT CISC as Neural Network Hardware Infrastructure
Taoran Xiang, Lunkai Zhang, Shuqian An +9
Neural Networks (NN) have been proven to be powerful tools to analyze Big Data. However, traditional CPUs cannot achieve the desired performance and/or energy efficiency for NN app…
cs.CV2020
Pixel-Semantic Revise of Position Learning A One-Stage Object Detector with A Shared Encoder-Decoder
Qian Li, Nan Guo, Xiaochun Ye +2
Recently, many methods have been proposed for object detection. They cannot detect objects by semantic features, adaptively. In this work, according to channel and spatial attentio…