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[FEA] Batching NN Descent #2403
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divyegala
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Aug 19, 2024
divyegala
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Aug 20, 2024
divyegala
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Aug 21, 2024
cjnolet
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Aug 22, 2024
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So sorry for being so late to review this @jinsolp. I think this is very close, but in order for this to be useful to users, we should make it as easy as possible to use and document very clearly what the algorithms does (and why a user would want to use it).
cjnolet
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Aug 22, 2024
/merge |
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adds the following parameters as part of the `build_kwds` - `n_clusters`: number of clusters to use when batching. Larger number of clusters reduce GPU memory usage. Defaults to 1 (no batch) Results showing consistent trustworthiness scores for doing/not doing batching. Also note below that now UMAP can run with datasets that don't fit on the GPU. Putting the dataset on host and enabling the batching method allows UMAP to run with a dataset that is 50M x 768 (153GB). <img width="709" alt="Screenshot 2024-08-13 at 5 55 27 PM" src="https://github.com/user-attachments/assets/39263583-4ffc-4b0b-886f-f1b0f21a99be"> ### Notes [This PR in raft](rapidsai/raft#2403) needs to be merged before this PR Authors: - Jinsol Park (https://github.com/jinsolp) Approvers: - Corey J. Nolet (https://github.com/cjnolet) - Dante Gama Dessavre (https://github.com/dantegd) URL: #6022
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This PR is an amalgamation of the diff of 3 PRs in RAFT: 1. rapidsai/raft#2345 2. rapidsai/raft#2380 3. rapidsai/raft#2403 This PR also addresses part 1 and 2 of #419, closes #391 and makes CAGRA use the compiled headers of NN Descent, which seemed to have been a pending TODO https://github.com/rapidsai/cuvs/blob/009bb8de03ce9708d4d797166187250f77a59a36/cpp/src/neighbors/detail/cagra/cagra_build.cuh#L36-L37 Also, batch tests are disabled in this PR due to issue rapidsai/raft#2450. PR #424 will attempt to re-enable them. Authors: - Divye Gala (https://github.com/divyegala) - Corey J. Nolet (https://github.com/cjnolet) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: #421
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cpp
improvement
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Description
This PR implements batching NN Descent. It will be helpful for reducing device memory usages for large datasets (specifically if the dataset is kept on host).
index_params
now has...n_clusters
: number of clusters to make. Larger clusters reduce device memory usage. Default is 1, in which case it doesn't do the batched NND.Notes
max_duplicates
forcheck_unique_indices
in testsBenchmarks