Reducing Communication in Graph Neural Network Training

Reducing Communication in Graph Neural Network Training

7 May 2020

Katherine Yelick

Papers citing "Reducing Communication in Graph Neural Network Training"

18 / 18 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
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
PID-Comm: A Fast and Flexible Collective Communication Framework for Commodity Processing-in-DIMM Devices Si Ung Noh Junguk Hong Chaemin Lim Seong-Yeol Park Jeehyun Kim Hanjun Kim Youngsok Kim Jinho Lee 34 6 0 13 Apr 2024
RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs Benjamin Brock A. Buluç Katherine Yelick 23 2 0 29 Nov 2023
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation Rui Xue Haoyu Han MohamadAli Torkamani Jian Pei Xiaorui Liu GNN 31 19 0 03 Feb 2023
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
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis Maciej Besta Torsten Hoefler GNN 34 56 0 19 May 2022
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 72 40 0 16 May 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 31 75 0 21 Mar 2022
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
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
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 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 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
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-Wei Zhang George Karypis FedML GNN 21 243 0 11 Oct 2020
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
Demystifying Graph Databases: Analysis and Taxonomy of Data Organization, System Designs, and Graph Queries Maciej Besta Robert Gerstenberger E. Peter Marc Fischer Michal Podstawski Claude Barthels Gustavo Alonso Torsten Hoefler GNN 25 92 0 20 Oct 2019
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 206 746 0 03 Sep 2019