arXiv Machine Learning July 21, 2026 By Pranjal Naman, Yogesh Simmhan

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

Read the original on arXiv Machine Learning →

arXiv:2607. 17374v1 Announce Type: cross Abstract: 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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

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SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction

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