RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations

19 October 2022

Daochen Zha

Papers citing "RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations"

21 / 21 papers shown

Title
Monarch: Expressive Structured Matrices for Efficient and Accurate Training Tri Dao Beidi Chen N. Sohoni Arjun D Desai Michael Poli Jessica Grogan Alexander Liu Aniruddh Rao Atri Rudra Christopher Ré 71 90 0 01 Apr 2022
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 61 75 0 21 Mar 2022
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication Cheng Wan Youjie Li Cameron R. Wolfe Anastasios Kyrillidis Namjae Kim Yingyan Lin GNN 46 67 0 20 Mar 2022
G-Mixup: Graph Data Augmentation for Graph Classification Xiaotian Han Zhimeng Jiang Ninghao Liu Xia Hu 35 195 0 15 Feb 2022
FMP: Toward Fair Graph Message Passing against Topology Bias Zhimeng Jiang Xiaotian Han Chao Fan Zirui Liu Na Zou Ali Mostafavi Xia Hu 38 48 0 08 Feb 2022
Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks M. Ramezani Weilin Cong Mehrdad Mahdavi M. Kandemir A. Sivasubramaniam GNN 40 32 0 16 Nov 2021
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 77 53 0 16 Oct 2021
Adaptive Label Smoothing To Regularize Large-Scale Graph Training Kaixiong Zhou Ninghao Liu Fan Yang Zirui Liu Rui Chen Li Li Soo-Hyun Choi Xia Hu AI4CE 34 19 0 30 Aug 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 53 119 0 14 Apr 2021
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 59 283 0 27 Oct 2020
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 43 245 0 11 Oct 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai Shengjie Luo Keyulu Xu Di He Tie-Yan Liu Liwei Wang GNN 65 161 0 07 Sep 2020
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 82 1,473 0 04 Jul 2020
Graph Random Neural Network for Semi-Supervised Learning on Graphs Wenzheng Feng Jie Zhang Yuxiao Dong Yu Han Huanbo Luan Qian Xu Qiang Yang Evgeny Kharlamov Jie Tang 74 391 0 22 May 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 194 2,701 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 80 282 0 17 Nov 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong Wenbing Huang Tingyang Xu Junzhou Huang 72 1,323 0 25 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 108 1,268 0 20 May 2019
Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera Aleksandar Bojchevski Stephan Günnemann GNN 190 1,674 0 14 Oct 2018
Faster Neural Network Training with Approximate Tensor Operations Menachem Adelman Kfir Y. Levy Ido Hakimi M. Silberstein 56 26 0 21 May 2018
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 231 6,628 0 08 Jun 2015