Accelerating Graph Sampling for Graph Machine Learning using GPUs

14 September 2020

Papers citing "Accelerating Graph Sampling for Graph Machine Learning using GPUs"

8 / 8 papers shown

Title
GraphScale: A Framework to Enable Machine Learning over Billion-node Graphs Vipul Gupta Xin Chen Ruoyun Huang Fanlong Meng Jianjun Chen Yujun Yan GNN 17 0 0 22 Jul 2024
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
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 11 11 0 28 Mar 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
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 27 59 0 01 Mar 2022
MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks R. Waleffe J. Mohoney Theodoros Rekatsinas Shivaram Venkataraman GNN 11 24 0 04 Feb 2022
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 Yanghua Peng Hongzheng Chen Hongzhi Chen Chuanxiong Guo GNN 26 69 0 16 Dec 2021
Scalable Graph Neural Network Training: The Case for Sampling Marco Serafini Hui Guan GNN 36 23 0 05 May 2021