Scalable Graph Neural Network Training: The Case for Sampling

5 May 2021

Papers citing "Scalable Graph Neural Network Training: The Case for Sampling"

9 / 9 papers shown

Title
Reducing Memory Contention and I/O Congestion for Disk-based GNN Training Qisheng Jiang Lei Jia Chundong Wang GNN 19 1 0 20 Jun 2024
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware Shichang Zhang Atefeh Sohrabizadeh Cheng Wan Zijie Huang Ziniu Hu Yewen Wang Yingyan Lin Lin Jason Cong Yizhou Sun GNN AI4CE 29 22 0 24 Jun 2023
The Evolution of Distributed Systems for Graph Neural Networks and their Origin in Graph Processing and Deep Learning: A Survey Jana Vatter R. Mayer Hans-Arno Jacobsen GNN AI4TS AI4CE 31 23 0 23 May 2023
Distributed Graph Embedding with Information-Oriented Random Walks Peng Fang Arijit Khan Siqiang Luo Fang Wang Dan Feng Zhenli Li Wei Yin Yu Cao GNN 11 11 0 28 Mar 2023
Towards a GML-Enabled Knowledge Graph Platform Hussein Abdallah Essam Mansour 16 2 0 03 Mar 2023
Scalable Graph Convolutional Network Training on Distributed-Memory Systems G. Demirci Aparajita Haldar Hakan Ferhatosmanoglu GNN 17 9 0 09 Dec 2022
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis Maciej Besta Torsten Hoefler GNN 32 54 0 19 May 2022
A Practical Tutorial on Graph Neural Networks I. Ward J. Joyner C. Lickfold Yulan Guo Bennamoun GNN AI4CE 14 12 0 11 Oct 2020
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 184 731 0 03 Sep 2019