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Show HN: Graphlearn-for-PyTorch, distributed graph learning on PyTorch
Hello HN,
We are pleased to introduce you graphlearn-for-pytorch (https://github.com/alibaba/graphlearn-for-pytorch https://github.com/alibaba/graphlearn-for-pytorch), an open-source distributed graph neural network library based on PyTorch and compatible with PyG. Our library is designed to make it easy for developers to build and train large-scale graph models in a distributed environment. With graphlearn-for-pytorch, you can leverage GPUs to accelerate graph sampling and utilize UVA to reduce the overheads of feature collection. Following a scalable design, graphlearn-for-pytorch supports training GNN models on multiple GPUs or even multiple machines. We have added some examples to demonstrate how to train PyG models in the distributed setting.
You are welcome to try it out and give us your feedback, tell us your feature requests and report bugs!
- sighingnow 3y agoOptimizing distributed sampling and feature lookup looks really attractive. It's really challenging to deploy GNN training at an industrial-scale for a large graph. Will GLT be part of graphscope[1] and replacing the current graphscope-for-learning implementation? [1]: https://github.com/alibaba/GraphScope https://github.com/alibaba/GraphScope
- lisu_sl 3y ago[dead]