Pre-propagation GNNs, whose training is bottlenecked by data loading, can be sped up roughly 15x with custom loaders, GPU double buffering, chunk reshuffling, and direct storage access, beating sampling-based GNNs by up to two orders of magnitude in throughput at comparable accuracy.
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
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Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs
Pre-propagation GNNs, whose training is bottlenecked by data loading, can be sped up roughly 15x with custom loaders, GPU double buffering, chunk reshuffling, and direct storage access, beating sampling-based GNNs by up to two orders of magnitude in throughput at comparable accuracy.