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MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel
  Communication-Computation Pipelining on Multi-GPU Platforms

MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms

14 September 2022
Yuke Wang
Boyuan Feng
Zheng Wang
Tong Geng
Kevin J. Barker
Ang Li
Yufei Ding
    GNN
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Papers citing "MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms"

3 / 3 papers shown
Title
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for
  Graph Neural Network Training
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training
Kezhao Huang
Haitian Jiang
Minjie Wang
Guangxuan Xiao
David Wipf
Xiang Song
Quan Gan
Zengfeng Huang
Jidong Zhai
Zheng-Wei Zhang
GNN
23
2
0
18 Jan 2023
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs
Chunyang Wang
Desen Sun
Yunru Bai
GNN
AI4CE
23
14
0
01 Jan 2023
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang
Da Zheng
Zihao Ye
Quan Gan
Mufei Li
...
J. Zhao
Haotong Zhang
Alex Smola
Jinyang Li
Zheng-Wei Zhang
AI4CE
GNN
182
731
0
03 Sep 2019
1