DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

14 April 2021

Papers citing "DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks"

20 / 20 papers shown

Title
Sparsity-Aware Communication for Distributed Graph Neural Network Training Ujjaini Mukhodopadhyay Alok Tripathy Oguz Selvitopi Katherine Yelick A. Buluç 39 1 0 07 Apr 2025
Graph Neural Networks Gone Hogwild Olga Solodova Nick Richardson Deniz Oktay Ryan P. Adams AI4CE GNN 19 1 0 29 Jun 2024
Anomaly Detection in Dynamic Graphs: A Comprehensive Survey Ocheme Anthony Ekle William Eberle AI4TS 27 10 0 31 May 2024
Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning Zezhong Ding Yongan Xiang Shangyou Wang Xike Xie S. K. Zhou 21 3 0 28 Feb 2024
CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph Databases and Analytics Milad Rezaei Hajidehi Sraavan Sridhar Margo Seltzer 28 2 0 13 Dec 2023
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training Nikolai Merkel Daniel Stoll R. Mayer Hans-Arno Jacobsen GNN 19 1 0 29 Aug 2023
SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding Xiangshan Chen Yongxiang Liao Yun Xiong Yao Zhang Si-Yuan Zhang Jiawei Zhang Yiheng Sun 19 6 0 27 Aug 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
Partitioner Selection with EASE to Optimize Distributed Graph Processing Nikolai Merkel R. Mayer Tawkir Ahmed Fakir Hans-Arno Jacobsen 24 5 0 11 Apr 2023
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
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science Santiago Miret Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings 27 19 0 31 Oct 2022
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
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan Zirui Liu Peihao Wang Wenqing Zheng Kaixiong Zhou Tianlong Chen Xia Hu Zhangyang Wang GNN 25 57 0 14 Oct 2022
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis Maciej Besta Torsten Hoefler GNN 32 55 0 19 May 2022
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 59 39 0 16 May 2022
FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems Rui Ma E. Georganas A. Heinecke Andrew Boutros Eriko Nurvitadhi GNN 14 11 0 22 Apr 2022
Scaling Knowledge Graph Embedding Models Nasrullah Sheikh Xiao Qin B. Reinwald Chuan Lei 31 5 0 08 Jan 2022
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs Da Zheng Xiang Song Chengrun Yang Dominique LaSalle George Karypis 3DH GNN 19 54 0 31 Dec 2021
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
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 231 3,230 0 24 Nov 2016