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Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching. (arXiv:2208.09151v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
Recently, Graph Neural Networks (GNNs) have been receiving a spotlight as a
powerful tool that can effectively serve various inference tasks on graph
structured data. As the size of real-world graphs continues to scale, the GNN
training system faces a scalability challenge. Distributed training is a
popular approach to address this challenge by scaling out CPU nodes. However,
not much attention has been paid to disk-based GNN training, which can scale up
the single-node system in a more cost-effective manner …
arxiv graph graph neural network lg machine memory network network training neural network scale ssd training