SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization

9 July 2020

Papers citing "SGQuant: Squeezing the Last Bit on Graph Neural Networks with Specialized Quantization"

6 / 6 papers shown

Title
Better Schedules for Low Precision Training of Deep Neural Networks Cameron R. Wolfe Anastasios Kyrillidis 45 1 0 04 Mar 2024
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation Shuang Wang B. Eravcı Rustam Guliyev Hakan Ferhatosmanoglu GNN MQ 19 6 0 29 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 40 23 0 23 May 2023
$$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks$ $\rm A^2Q$ : Aggregation-Aware Quantization for Graph Neural Networks Zeyu Zhu Fanrong Li Zitao Mo Qinghao Hu Gang Li Zejian Liu Xiaoyao Liang Jian Cheng GNN MQ 21 4 0 01 Feb 2023
QGTC: Accelerating Quantized Graph Neural Networks via GPU Tensor Core Yuke Wang Boyuan Feng Yufei Ding GNN 33 41 0 18 Nov 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization Mucong Ding Kezhi Kong Jingling Li Chen Zhu John P. Dickerson Furong Huang Tom Goldstein GNN MQ 27 47 0 27 Oct 2021