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DistDGL: Distributed Graph Neural Network Training for Billion-Scale
  Graphs

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs

11 October 2020
Da Zheng
Chao Ma
Minjie Wang
Jinjing Zhou
Qidong Su
Xiang Song
Quan Gan
Zheng-Wei Zhang
George Karypis
    FedML
    GNN
ArXivPDFHTML

Papers citing "DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs"

47 / 47 papers shown
Title
Deal: Distributed End-to-End GNN Inference for All Nodes
Shiyang Chen
Xiang Song
Vasiloudis Theodore
Hang Liu
GNN
50
0
0
04 Mar 2025
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks
Pau Ferrer-Cid
Jose M. Barcelo-Ordinas
J. García-Vidal
42
2
0
28 Oct 2024
CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph
  Databases and Analytics
CUTTANA: Scalable Graph Partitioning for Faster Distributed Graph Databases and Analytics
Milad Rezaei Hajidehi
Sraavan Sridhar
Margo Seltzer
35
2
0
13 Dec 2023
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for
  Graph Streams
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams
Chaoyi Chen
Dechao Gao
Yanfeng Zhang
Qiange Wang
Zhenbo Fu
Xuecang Zhang
Junhua Zhu
Yu Gu
Ge Yu
GNN
43
5
0
05 Dec 2023
An Experimental Comparison of Partitioning Strategies for Distributed
  Graph Neural Network Training
An Experimental Comparison of Partitioning Strategies for Distributed Graph Neural Network Training
Nikolai Merkel
Daniel Stoll
R. Mayer
Hans-Arno Jacobsen
GNN
27
1
0
29 Aug 2023
SPEED: Streaming Partition and Parallel Acceleration for Temporal
  Interaction Graph Embedding
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
23
6
0
27 Aug 2023
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training
Hongkuan Zhou
Da Zheng
Xiang Song
George Karypis
Viktor Prasanna
GNN
29
13
0
14 Jul 2023
Pitfalls in Link Prediction with Graph Neural Networks: Understanding
  the Impact of Target-link Inclusion & Better Practices
Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices
Jing Zhu
Yuhang Zhou
V. Ioannidis
Sheng Qian
Wei Ai
Xiang Song
Danai Koutra
25
9
0
01 Jun 2023
The Evolution of Distributed Systems for Graph Neural Networks and their
  Origin in Graph Processing and Deep Learning: A Survey
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
48
23
0
23 May 2023
Distributed Graph Embedding with Information-Oriented Random Walks
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
18
11
0
28 Mar 2023
HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA
  Heterogeneous Platform
HitGNN: High-throughput GNN Training Framework on CPU+Multi-FPGA Heterogeneous Platform
Yi-Chien Lin
Bingyi Zhang
Viktor Prasanna
GNN
29
5
0
02 Mar 2023
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size
  of Public Graph Datasets for Deep Learning Research
IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research
Arpandeep Khatua
Vikram Sharma Mailthody
Bhagyashree Taleka
Tengfei Ma
Xiang Song
Wen-mei W. Hwu
AI4CE
48
37
0
27 Feb 2023
Reply to: Inability of a graph neural network heuristic to outperform
  greedy algorithms in solving combinatorial optimization problems
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems
M. Schuetz
J. K. Brubaker
H. Katzgraber
33
2
0
03 Feb 2023
Reply to: Modern graph neural networks do worse than classical greedy
  algorithms in solving combinatorial optimization problems like maximum
  independent set
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set
M. Schuetz
J. K. Brubaker
H. Katzgraber
31
10
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
33
2
0
18 Jan 2023
Tuning the Tail Latency of Distributed Queries Using Replication
Tuning the Tail Latency of Distributed Queries Using Replication
Nathan Ng
Hung-Cuong Le
Marco Serafini
16
0
0
20 Dec 2022
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
22
0
0
11 Dec 2022
DGI: Easy and Efficient Inference for GNNs
DGI: Easy and Efficient Inference for GNNs
Peiqi Yin
Xiao Yan
Jinjing Zhou
Qiang Fu
Zhenkun Cai
James Cheng
Bo Tang
Minjie Wang
GNN
30
4
0
28 Nov 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
46
5
0
25 Nov 2022
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86
  via Minibatch Sampling
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling
Md. Vasimuddin
Ramanarayan Mohanty
Sanchit Misra
Sasikanth Avancha
GNN
18
1
0
11 Nov 2022
Distributed Graph Neural Network Training: A Survey
Distributed Graph Neural Network Training: A Survey
Yingxia Shao
Hongzheng Li
Xizhi Gu
Hongbo Yin
Yawen Li
Xupeng Miao
Wentao Zhang
Bin Cui
Lei Chen
GNN
AI4CE
11
56
0
01 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
32
15
0
19 Oct 2022
Analysis and Optimization of GNN-Based Recommender Systems on Persistent
  Memory
Analysis and Optimization of GNN-Based Recommender Systems on Persistent Memory
Yuwei Hu
Jiajie Li
Zhongming Yu
Zhiru Zhang
GNN
39
0
0
25 Jul 2022
TF-GNN: Graph Neural Networks in TensorFlow
TF-GNN: Graph Neural Networks in TensorFlow
Oleksandr Ferludin
Arno Eigenwillig
Martin J. Blais
Dustin Zelle
Jan Pfeifer
...
Anton Tsitsulin
Kevin Villela
Lisa Wang
David Wong
Bryan Perozzi
GNN
18
35
0
07 Jul 2022
Graph Attention Multi-Layer Perceptron
Graph Attention Multi-Layer Perceptron
Wentao Zhang
Ziqi Yin
Zeang Sheng
Yang Li
Wenbin Ouyang
Xiaosen Li
Yangyu Tao
Zhi-Xin Yang
Bin Cui
GNN
AI4CE
35
99
0
09 Jun 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
34
56
0
19 May 2022
SmartSAGE: Training Large-scale Graph Neural Networks using In-Storage
  Processing Architectures
SmartSAGE: Training Large-scale Graph Neural Networks using In-Storage Processing Architectures
Yunjae Lee
Jin-Won Chung
Minsoo Rhu
GNN
29
48
0
10 May 2022
TGL: A General Framework for Temporal GNN Training on Billion-Scale
  Graphs
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs
Hongkuan Zhou
Da Zheng
Israt Nisa
Vasileios Ioannidis
Xiang Song
George Karypis
AI4CE
39
86
0
28 Mar 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
34
75
0
21 Mar 2022
Towards Training Billion Parameter Graph Neural Networks for Atomic
  Simulations
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
Anuroop Sriram
Abhishek Das
Brandon M. Wood
Siddharth Goyal
C. L. Zitnick
AI4CE
33
27
0
18 Mar 2022
PaSca: a Graph Neural Architecture Search System under the Scalable
  Paradigm
PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm
Wentao Zhang
Yu Shen
Zheyu Lin
Yang Li
Xiaosen Li
Wenbin Ouyang
Yangyu Tao
Zhi-Xin Yang
Bin Cui
GNN
40
59
0
01 Mar 2022
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
Xin Liu
Yurui Lai
Lei Deng
Guoqi Li
Xiaochun Ye
Xiaochun Ye
Shirui Pan
Yuan Xie
GNN
16
41
0
10 Feb 2022
MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural
  Networks
MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks
R. Waleffe
J. Mohoney
Theodoros Rekatsinas
Shivaram Venkataraman
GNN
26
25
0
04 Feb 2022
Scaling Knowledge Graph Embedding Models
Scaling Knowledge Graph Embedding Models
Nasrullah Sheikh
Xiao Qin
B. Reinwald
Chuan Lei
39
5
0
08 Jan 2022
Distributed Hybrid CPU and GPU training for Graph Neural Networks on
  Billion-Scale Graphs
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
32
56
0
31 Dec 2021
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and
  Preprocessing
BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing
Tianfeng Liu
Yangrui Chen
Dan Li
Chuan Wu
Yibo Zhu
Jun He
Size Zheng
Hongzheng Chen
Hongzhi Chen
Chuanxiong Guo
GNN
34
77
0
16 Dec 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph
  Parameters
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Takanori Maehara
Hoang NT
41
2
0
05 Nov 2021
Accelerating Training and Inference of Graph Neural Networks with Fast
  Sampling and Pipelining
Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining
Tim Kaler
Nickolas Stathas
Anne Ouyang
A. Iliopoulos
Tao B. Schardl
C. E. Leiserson
Jie Chen
GNN
70
53
0
16 Oct 2021
Evaluating Deep Graph Neural Networks
Evaluating Deep Graph Neural Networks
Wentao Zhang
Zeang Sheng
Yuezihan Jiang
Yikuan Xia
Jun Gao
Zhi-Xin Yang
Bin Cui
GNN
AI4CE
21
31
0
02 Aug 2021
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
Combinatorial Optimization with Physics-Inspired Graph Neural Networks
M. Schuetz
J. K. Brubaker
H. Katzgraber
AI4CE
28
177
0
02 Jul 2021
OpenGraphGym-MG: Using Reinforcement Learning to Solve Large Graph
  Optimization Problems on MultiGPU Systems
OpenGraphGym-MG: Using Reinforcement Learning to Solve Large Graph Optimization Problems on MultiGPU Systems
Weijian Zheng
Dali Wang
Fengguang Song
GNN
OffRL
AI4CE
18
1
0
18 May 2021
Scalable Graph Neural Network Training: The Case for Sampling
Scalable Graph Neural Network Training: The Case for Sampling
Marco Serafini
Hui Guan
GNN
41
23
0
05 May 2021
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
44
11
0
21 Apr 2021
GMLP: Building Scalable and Flexible Graph Neural Networks with
  Feature-Message Passing
GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing
Wentao Zhang
Yu Shen
Zheyu Lin
Yang Li
Xiaosen Li
Wenbin Ouyang
Yangyu Tao
Zhi-Xin Yang
Bin Cui
27
9
0
20 Apr 2021
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural
  Networks
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks
Vasimuddin
Sanchit Misra
Guixiang Ma
Ramanarayan Mohanty
E. Georganas
A. Heinecke
Dhiraj D. Kalamkar
Nesreen Ahmed
Sasikanth Avancha
GNN
33
119
0
14 Apr 2021
Large Graph Convolutional Network Training with GPU-Oriented Data
  Communication Architecture
Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture
S. Min
Kun Wu
Sitao Huang
Mert Hidayetouglu
Jinjun Xiong
Eiman Ebrahimi
Deming Chen
Wen-mei W. Hwu
GNN
10
67
0
04 Mar 2021
Computing Graph Neural Networks: A Survey from Algorithms to
  Accelerators
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators
S. Abadal
Akshay Jain
Robert Guirado
Jorge López-Alonso
Eduard Alarcón
GNN
30
225
0
30 Sep 2020
1