Pranjal Naman

Taurus: Accelerating Out-of-Core Graph Neural Network Inference on Billion-Scale Graphs

Pranjal Naman, Yogesh Simmhan

Graph Neural Network (GNN) inference on billion-scale graphs is challenging due to the large memory footprint of features and embeddings and high disk I/O costs in out-of-core settings. Existing distributed GNN systems incur high communication times and infrastructure costs, whil…Read more