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doc: add doc to use GPU for indexing (#611)
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@@ -71,9 +71,41 @@ a single PQ code.
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### Use GPU to build vector index
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Lance Python SDK has experimental GPU support for creating IVF index.
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Using GPU for index creation requires [PyTorch>2.0](https://pytorch.org/) being installed.
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You can specify the GPU device to train IVF partitions via
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- **accelerator**: Specify to `"cuda"`` to enable GPU training.
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- **accelerator**: Specify to ``cuda`` or ``mps`` (on Apple Silicon) to enable GPU training.
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=== "Linux"
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<!-- skip-test -->
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``` { .python .copy }
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# Create index using CUDA on Nvidia GPUs.
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tbl.create_index(
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num_partitions=256,
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num_sub_vectors=96,
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accelerator="cuda"
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)
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```
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=== "Macos"
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<!-- skip-test -->
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```python
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# Create index using MPS on Apple Silicon.
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tbl.create_index(
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num_partitions=256,
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num_sub_vectors=96,
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accelerator="mps"
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)
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```
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Trouble shootings:
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If you see ``AssertionError: Torch not compiled with CUDA enabled``, you need to [install
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PyTorch with CUDA support](https://pytorch.org/get-started/locally/).
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## Querying an ANN Index
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