10 citations · 16 across the 7 of their papers we have counts for
3 papers · 1 filter
Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks
Roger Waleffe, Devesh Sarda, Jason Mohoney +3
We study distributed training of Graph Neural Networks (GNNs) on billion-scale graphs that are partitioned across machines. Efficient training in this setting relies on min-edge-cu…
MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks
Roger Waleffe, Jason Mohoney, Theodoros Rekatsinas +1
We study training of Graph Neural Networks (GNNs) for large-scale graphs. We revisit the premise of using distributed training for billion-scale graphs and show that for graphs tha…
Marius: Learning Massive Graph Embeddings on a Single Machine
Jason Mohoney, Roger Waleffe, Yiheng Xu +2
We propose a new framework for computing the embeddings of large-scale graphs on a single machine. A graph embedding is a fixed length vector representation for each node (and/or e…