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 ...

Jul 14, 2021 · We propose a new framework for computing the em- beddings of large-scale graphs on a single machine. A graph embedding is a fixed length ...

Marius (OSDI '21 Paper) is designed to mitigate/reduce data movement overheads for graph embeddings using: Pipelined training and IO; Partition caching and a ...

Aug 11, 2021 · This demon- stration showcases Marius: a new open-source engine for learning graph embedding models over billion-edge graphs on a single ma-.

Jul 1, 2021 · This demonstration showcases Marius: a new open-source engine for learning graph embedding models over billion-edge graphs on a single machine.

This demon- stration showcases Marius: a new open-source engine for learning graph embedding models over billion-edge graphs on a single ma- chine. Marius is ...

Large-scale Graph Learning in a Single Machine. We are developing Marius to make the use of deep learning models over billion-scale graphs easier, faster, ...

Marius: Learning massive graph embeddings on a single machine. J Mohoney, R Waleffe, H Xu, T Rekatsinas, S Venkataraman. 15th {USENIX} Symposium on Operating ...

Demo of Marius: A System for Large-scale Graph Embeddings Anze Xie et al. VLDB demo 21; Marius: Learning Massive Graph Embeddings on a Single Machine Jason ...