[GraphBolt][CUDA] Refactor overlap_graph_fetch, simplify gb.DataLoader.
#7681
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To trigger regression tests:
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mfbalin
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the
expedited
mfbalin
commented
Aug 11, 2024
frozenbugs
reviewed
Aug 16, 2024
| @@ -134,16 +134,14 @@ def create_dataloader( | |||
| ############################################################################ | |||
| if args.storage_device != "cpu": | |||
| datapipe = datapipe.copy_to(device) | |||
| datapipe = datapipe.sample_neighbor(graph, args.fanout) | |||
| datapipe = datapipe.sample_neighbor( | |||
| graph, args.fanout, overlap_fetch=args.storage_device == "pinned" | |||
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Did we release the overlap_fetch in last release, if so, we need to highlight the API change if we really believe this is a good api change.
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I think it is in DGL 2.3. In this release, this parameter moved from gb.DataLoader to sample_neighbor.
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https://docs.dgl.ai/en/latest/generated/dgl.graphbolt.DataLoader.html#dgl.graphbolt.DataLoader shows the overlap_graph_fetch option.
lijialin03
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Jan 6, 2025
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Description
gb.DataLoaderto the sampling classes foroverlap_graph_fetch. It is an argument of the sampler now.gpu_graph_cacheto the FusedCSCSamplingGraph because otherwise it won't be shared across train or validation dataloader for example. That way, there will be a single graph cache for multiple dataloader instances.The end goal is to make sampling and compaction async and hide the latency of GPU CPU synchronizations during these stages. A lot of our optimizations also have inherent GPU CPU synchronization, which will be handled in the same way. I needed to clean the code and refactor before #7682.
I might refactor more and reduce the amount of code in our code base in the future.
Checklist
Please feel free to remove inapplicable items for your PR.
Changes