4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2023
Cooperative Minibatching in Graph Neural Networks
Muhammed Fatih Balin, Dominique LaSalle, Ümit V. Çatalyürek
Training large scale Graph Neural Networks (GNNs) requires significant computational resources, and the process is highly data-intensive. One of the most effective ways to reduce r…
cs.DC2021★ 4 cited
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs
Da Zheng, Xiang Song, Chengru Yang +2
Graph neural networks (GNN) have shown great success in learning from graph-structured data. They are widely used in various applications, such as recommendation, fraud detection,…