2021
GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
ICML 2021spotlight
We present GNNAutoScale (GAS), a framework for scaling arbitrary message-passing GNNs to large graphs. GAS prunes entire sub-trees of the computation graph by utilizing historical embeddings from prior training iterations, leading to constant GPU memory consumption in respect to input node size with…