Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching

4 May 2023

Jie Chen

Papers citing "Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching"

22 / 22 papers shown

Title
Graph Neural Preconditioners for Iterative Solutions of Sparse Linear Systems Jie Chen AI4CE 211 4 0 28 Jan 2025
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 89 76 0 21 Mar 2022
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 101 55 0 16 Oct 2021
Global Neighbor Sampling for Mixed CPU-GPU Training on Giant Graphs Jialin Dong Da Zheng Lin F. Yang Geroge Karypis GNN 38 37 0 11 Jun 2021
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 63 122 0 14 Apr 2021
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs Weihua Hu Matthias Fey Hongyu Ren Maho Nakata Yuxiao Dong J. Leskovec AI4CE 72 413 0 17 Mar 2021
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 57 68 0 04 Mar 2021
Marius: Learning Massive Graph Embeddings on a Single Machine J. Mohoney R. Waleffe Yiheng Xu Theodoros Rekatsinas Shivaram Venkataraman GNN 97 62 0 20 Jan 2021
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs Da Zheng Chao Ma Minjie Wang Jinjing Zhou Qidong Su Xiang Song Quan Gan Zheng Zhang George Karypis FedML GNN 59 248 0 11 Oct 2020
GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs Yuke Wang Boyuan Feng Gushu Li Shuangchen Li Lei Deng Yuan Xie Yufei Ding GNN 89 123 0 11 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 306 2,732 0 02 May 2020
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks Difan Zou Ziniu Hu Yewen Wang Song Jiang Yizhou Sun Quanquan Gu GNN 95 283 0 17 Nov 2019
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics Mark Weber Giacomo Domeniconi Jie Chen D. Weidele Claudio Bellei Tom Robinson C. E. Leiserson 69 326 0 31 Jul 2019
GraphSAINT: Graph Sampling Based Inductive Learning Method Hanqing Zeng Hongkuan Zhou Ajitesh Srivastava Rajgopal Kannan Viktor Prasanna GNN 137 966 0 10 Jul 2019
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks Wei-Lin Chiang Xuanqing Liu Si Si Yang Li Samy Bengio Cho-Jui Hsieh GNN 147 1,273 0 20 May 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 243 7,653 0 01 Oct 2018
Graph Convolutional Neural Networks for Web-Scale Recommender Systems Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L. Hamilton J. Leskovec GNN BDL 263 3,540 0 06 Jun 2018
FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling Jie Chen Tengfei Ma Cao Xiao GNN 144 1,513 0 30 Jan 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,164 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 509 15,247 0 07 Jun 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 593 7,455 0 04 Apr 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 641 29,076 0 09 Sep 2016