BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing

16 December 2021

Papers citing "BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing"

7 / 7 papers shown

Title
Efficient GNN Training Through Structure-Aware Randomized Mini-Batching Vignesh Balaji Christos Kozyrakis Gal Chechik Haggai Maron GNN 30 0 0 25 Apr 2025
Towards providing reliable job completion time predictions using PCS Abdullah Bin Faisal Noah Martin Hafiz Mohsin Bashir Swaminathan Lamelas Fahad R. Dogar 15 0 0 18 Jan 2024
SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding Xiangshan Chen Yongxiang Liao Yun Xiong Yao Zhang Si-Yuan Zhang Jiawei Zhang Yiheng Sun 6 6 0 27 Aug 2023
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 16 23 0 23 May 2023
Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis Maciej Besta Torsten Hoefler GNN 27 54 0 19 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 34 98 0 16 May 2022
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 177 731 0 03 Sep 2019