C-SAW: A Framework for Graph Sampling and Random Walk on GPUs

18 September 2020

Papers citing "C-SAW: A Framework for Graph Sampling and Random Walk on GPUs"

5 / 5 papers shown

Title
Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours Yuxin Yang Hongkuan Zhou R. Kannan Viktor Prasanna 25 0 0 31 Dec 2024
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
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 184 731 0 03 Sep 2019
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 184 878 0 07 Jun 2018