Distributed Sampling in cuGraph-PyG #4384
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tingyu66
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May 29, 2024
| sz = torch.tensor(num_vertices[vtype], device="cuda") | ||
| torch.distributed.all_reduce(sz, op=torch.distributed.ReduceOp.MAX) | ||
| num_vertices[vtype] = int(sz) | ||
| return num_vertices |
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Should we cache num_vertices and num_edges since they require collective communications?
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We cache the offsets, which are more frequently used, but I might add caching the vertex and edge counts if they are used more often. So maybe in the future.
BradReesWork
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May 29, 2024
AyodeAwe
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May 29, 2024
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Reimplements the WG feature store for PyG using the `FeatureStore` interface. Merge after #4384 Closes rapidsai/wholegraph#47 Closes #4399 Authors: - Alex Barghi (https://github.com/alexbarghi-nv) - Seunghwa Kang (https://github.com/seunghwak) - Tingyu Wang (https://github.com/tingyu66) - Ralph Liu (https://github.com/nv-rliu) Approvers: - Tingyu Wang (https://github.com/tingyu66) - Vibhu Jawa (https://github.com/VibhuJawa) - Brad Rees (https://github.com/BradReesWork) - Ray Douglass (https://github.com/raydouglass) URL: #4432
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Distributed sampling in cuGraph-PyG. Also renames the existing API to clarify that it is dask based.
Adds a dependency on
tensordictforcuGraph-PyGwhich supports the newTensorDictFeatureStore.Also no longer installs
torch-clusterandtorch-spline-convin CI for testing since that results in anImportErrorand neither of those packages are needed.Requires PyG 2.5. Should be merged after #4335
Merge after #4355
Closes #4248
Closes #4249
Closes #3383
Closes #3942
Closes #3836
Closes #4202
Closes #4051
Closes #4326
Closes #4252
Partially addresses #3805