DGL Files

We're thrilled to announce the release of DGL 2.1.0. 🎉🎉🎉

Major Changes:

1. CUDA backend of GraphBolt is now available. Thanks @mfbalin for the extraordinary effort. See the updated examples.
2. PyTorch 1.13 is not supported any more. The supported PyTorch versions are 2.0.0/1, 2.1.0/1/2, 2.2.0/1.
3. CUDA 11.6 is not supported any more. The supported CUDA versions are 11.7, 11.8, 12.1.
4. Data loading performance improvements via pipeline parallelism, operation/kernel optimizations and so on.
5. Add support for converting sampling output of GraphBolt to PyG data format and train with PyG models seamlessly: examples.

Bug Fixes

• [Grapbolt]Negative node pairs should be 2D by @peizhou001 in https://github.com/dmlc/dgl/pull/6951
• [GraphBolt] Fix fanouts setting in rgcn example by @RamonZhou in https://github.com/dmlc/dgl/pull/6959
• [GraphBolt] fix random generator for shuffle among all workers by @Rhett-Ying in https://github.com/dmlc/dgl/pull/6982
• [GraphBolt] fix preprocess issue for single ntype/etype graph by @Rhett-Ying in https://github.com/dmlc/dgl/pull/7011
• [GraphBolt] Fix gpu NegativeSampler for seeds. by @yxy235 in https://github.com/dmlc/dgl/pull/7068
• [GraphBolt][CUDA] Fix link prediction early-stop. by @mfbalin in https://github.com/dmlc/dgl/pull/7083

New Examples

• [Feature] ARGO: an easy-to-use runtime to improve GNN training performance on multi-core processors by @jasonlin316 in https://github.com/dmlc/dgl/pull/7003

Acknowledgement

Thanks for all your contributions. @drivanov @frozenbugs @LourensT @Skeleton003 @mfbalin @RamonZhou @Rhett-Ying @wkmyws @jasonlin316 @caojy1998 @czkkkkkk @hutiechuan @peizhou001 @rudongyu @xiangyuzhi @yxy235