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20222025
most citedSDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks

3 citations · 3 across the 5 of their papers we have counts for

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cs.LG2025

Demystifying Distributed Training of Graph Neural Networks for Link Prediction

Xin Huang, Chul-Ho Lee

Graph neural networks (GNNs) are powerful tools for solving graph-related problems. Distributed GNN frameworks and systems enhance the scalability of GNNs and accelerate model trai…

cs.LG2024★ 3 cited

SDT-GNN: Streaming-based Distributed Training Framework for Graph Neural Networks

Xin Huang, Weipeng Zhuo, Minh Phu Vuong +4

Recently, distributed GNN training frameworks, such as DistDGL and PyG, have been developed to enable training GNN models on large graphs by leveraging multiple GPUs in a distribut…

cs.LG2022

Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass

Xin Huang, Jongryool Kim, Bradley Rees +1

Graph neural networks (GNNs) have received great attention due to their success in various graph-related learning tasks. Several GNN frameworks have then been developed for fast an…