{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/629a6154b4e1e70012764c00/64c635e8fc49e20011956bea?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":" Roger Waleffe | MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks | #37","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/629a6154b4e1e70012764c00/1690710063978-668a16ca0eb5de71abf84df05f946861.jpeg?height=200","description":"<h3>Summary: </h3><p>In this episode, Roger Waleffe talks about Graph Neural Networks (GNNs) for large-scale graphs. Specifically, he reveals all about MariusGNN, the first system that utilises the entire storage hierarchy (including disk) for GNN training. Tune in to find out how MaruisGNN works and just how fast it goes (and how much more cost-efficient it is!) </p><p><br></p><p>Links: </p><ul><li><a href=\"https://marius-project.org/\" rel=\"noopener noreferrer\" target=\"_blank\">Marius Project</a></li><li><a href=\"http://www.rogerwaleffe.com/\" rel=\"noopener noreferrer\" target=\"_blank\">Roger's Homepage</a> </li><li><a href=\"https://twitter.com/RWaleffe\" rel=\"noopener noreferrer\" target=\"_blank\">Roger's Twitter</a></li><li><a href=\"https://arxiv.org/abs/2202.02365\" rel=\"noopener noreferrer\" target=\"_blank\">EuroSys'23 Paper</a></li></ul><p><br></p><p>Support the podcast through <a href=\"https://www.buymeacoffee.com/disseminate\" rel=\"noopener noreferrer\" target=\"_blank\">Buy Me a Coffee</a></p>","author_name":"Jack Waudby"}