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PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks
  with Pipelined Feature Communication

PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication

20 March 2022
Cheng Wan
Youjie Li
Cameron R. Wolfe
Anastasios Kyrillidis
Namjae Kim
Yingyan Lin
    GNN
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Papers citing "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication"

11 / 11 papers shown
Title
Graph Neural Networks Gone Hogwild
Graph Neural Networks Gone Hogwild
Olga Solodova
Nick Richardson
Deniz Oktay
Ryan P. Adams
AI4CE
GNN
19
1
0
29 Jun 2024
Better Schedules for Low Precision Training of Deep Neural Networks
Better Schedules for Low Precision Training of Deep Neural Networks
Cameron R. Wolfe
Anastasios Kyrillidis
35
1
0
04 Mar 2024
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph
  Representation Learning
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning
Haoteng Yin
Muhan Zhang
Jianguo Wang
Pan Li
61
8
0
06 Mar 2023
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation
Rui Xue
Haoyu Han
MohamadAli Torkamani
Jian Pei
Xiaorui Liu
GNN
20
19
0
03 Feb 2023
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
ABC: Aggregation before Communication, a Communication Reduction
  Framework for Distributed Graph Neural Network Training and Effective
  Partition
ABC: Aggregation before Communication, a Communication Reduction Framework for Distributed Graph Neural Network Training and Effective Partition
Junwei Su
GNN
14
0
0
11 Dec 2022
Extreme Acceleration of Graph Neural Network-based Prediction Models for
  Quantum Chemistry
Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry
Hatem Helal
J. Firoz
Jenna A. Bilbrey
M. M. Krell
Tom Murray
Ang Li
S. Xantheas
Sutanay Choudhury
GNN
23
5
0
25 Nov 2022
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse
  Computations
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations
Zirui Liu
Sheng-Wei Chen
Kaixiong Zhou
Daochen Zha
Xiao Huang
Xia Hu
24
14
0
19 Oct 2022
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency
  Analysis
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis
Maciej Besta
Torsten Hoefler
GNN
32
55
0
19 May 2022
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks
  with Partition-Parallelism and Random Boundary Node Sampling
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling
Cheng Wan
Youjie Li
Ang Li
Namjae Kim
Yingyan Lin
GNN
27
75
0
21 Mar 2022
GraphTheta: A Distributed Graph Neural Network Learning System With
  Flexible Training Strategy
GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy
Yongchao Liu
Houyi Li
Guowei Zhang
Xintan Zeng
Yongyong Li
...
Peng Zhang
Zhao Li
Kefeng Deng
Changhua He
Wenguang Chen
GNN
42
11
0
21 Apr 2021
1