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Aaron Lin
a695814f4c
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/issues/4450 This pull request introduces support for [Intel ScalableVectorSearch](https://github.com/intel/ScalableVectorSearch), integrating Intel's proprietary LVQ and LeanVec technologies in binary form. The following index types are now supported: `IndexSVSVamana`, `IndexSVSVamanaLVQ`, `IndexSVSVamanaLeanVec`, and `IndexSVSFlat`. `IndexSVSVamana` and `IndexSVSFlat` utilizes SVS open-source float32/float16/int8 implementation. Key features and enhancements include: - Implemented `search`, `add`, and `remove_ids` - Implemented filter search and `range_search` - Enabled SVS open-source fp16 and scalar quantization implementation - Enabled factory methods - Enabled save/load - Enabled Python bindings - Enable fallback mechanism that fallbacks to 8-bit scalar quantization if LVQ/LeanVec is used on non-intel hardware CPUs - Added examples in both Python and C++ under the `tutorial/` directory - Added `FAISS_ENABLE_SVS` flag to allows users to optionally enable SVS TODOs: - Support more indices such as `IndexSVSIVF` and `IndexSVSFlat` with LVQ and LeanVec - Documentation Pull Request resolved: https://github.com/facebookresearch/faiss/pull/4548 Reviewed By: subhadeepkaran Differential Revision: D84713772 Pulled By: mnorris11 fbshipit-source-id: 290365eb3337f685dd46696935b621c57dad3174