MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel
Communication-Computation Pipelining on Multi-GPU Platforms

MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms

14 September 2022

Zheng Wang

Kevin J. Barker

Papers citing "MGG: Accelerating Graph Neural Networks with Fine-grained intra-kernel Communication-Computation Pipelining on Multi-GPU Platforms"

4 / 4 papers shown

Title
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
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 28 2 0 18 Jan 2023
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs Chunyang Wang Desen Sun Yunru Bai GNN AI4CE 45 15 0 01 Jan 2023
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 194 745 0 03 Sep 2019