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Changelog

All notable changes to this project will be documented in this file.

Unreleased

1.9.0 - 2024-10-04

Added

  • Add AVX-512 implementation for the distance and scalar quantizer functions. (#3853)
  • Allow k and M suffixes in IVF indexes (#3812)
  • add reconstruct support to additive quantizers (#3752)
  • introduce options for reducing the overhead for a clustering procedure (#3731)
  • Add hnsw search params for bounded queue option (#3748)
  • ROCm support (#3462)
  • Add sve targets (#2886)
  • add get_version() for c_api (#3688)
  • QINCo implementation in CPU Faiss (#3608)
  • Add search functionality to FlatCodes (#3611)
  • add dispatcher for VectorDistance and ResultHandlers (#3627)
  • Add SQ8bit signed quantization (#3501)
  • Add ABS_INNER_PRODUCT metric (#3524)
  • Interop between CAGRA and HNSW (#3252)
  • add skip_storage flag to HNSW (#3487)
  • QT_bf16 for scalar quantizer for bfloat16 (#3444)
  • Implement METRIC.NaNEuclidean (#3414)
  • TimeoutCallback C++ and Python (#3417)
  • support big-endian machines (#3361)
  • Support for Remove ids from IVFPQFastScan index (#3354)
  • Implement reconstruct_n for GPU IVFFlat indexes (#3338)
  • Support of skip_ids in merge_from_multiple function of OnDiskInvertedLists (#3327)
  • Add the ability to clone and read binary indexes to the C API. (#3318)
  • AVX512 for PQFastScan (#3276)

Changed

  • faster hnsw CPU index training (#3822)
  • Some small improvements. (#3692)
  • First attempt at LSH matching with nbits (#3679)
  • Set verbosoe before train (#3619)
  • Remove duplicate NegativeDistanceComputer instances (#3450)
  • interrupt for NNDescent (#3432)
  • Get rid of redundant instructions in ScalarQuantizer (#3430)
  • PowerPC, improve code generation for function fvec_L2sqr (#3416)
  • Unroll loop in lookup_2_lanes (#3364)
  • Improve filtering & search parameters propagation (#3304)
  • Change index_cpu_to_gpu to throw for indices not implemented on GPU (#3336)
  • Throw when attempting to move IndexPQ to GPU (#3328)
  • Skip HNSWPQ sdc init with new io flag (#3250)

Fixed

  • FIx a bug for a non-simdlib code of ResidualQuantizer (#3868)
  • assign_index should default to null (#3855)
  • Fix an incorrectly counted the number of computed distances for HNSW (#3840)
  • Add error for overflowing nbits during PQ construction (#3833)
  • Fix radius search with HSNW and IP (#3698)
  • fix algorithm of spreading vectors over shards (#3374)
  • Fix IndexBinary.assign Python method (#3384)
  • Few fixes in bench_fw to enable IndexFromCodec (#3383)
  • Fix the endianness issue in AIX while running the benchmark. (#3345)
  • Fix faiss swig build with version > 4.2.x (#3315)
  • Fix problems when using 64-bit integers. (#3322)
  • Fix IVFPQFastScan decode function (#3312)
  • Handling FaissException in few destructors of ResultHandler.h (#3311)
  • Fix HNSW stats (#3309)
  • AIX compilation fix for io classes (#3275)

1.8.0 - 2024-02-27

Added

  • Added a new conda package faiss-gpu-raft alongside faiss-cpu and faiss-gpu
  • Integrated IVF-Flat and IVF-PQ implementations in faiss-gpu-raft from RAFT by Nvidia [thanks Corey Nolet and Tarang Jain]
  • Added a context parameter to InvertedLists and InvertedListsIterator
  • Added Faiss on Rocksdb demo to showing how inverted lists can be persisted in a key-value store
  • Introduced Offline IVF framework powered by Faiss big batch search
  • Added SIMD NEON Optimization for QT_FP16 in Scalar Quantizer. [thanks Naveen Tatikonda]
  • Generalized ResultHandler and supported range search for HNSW and FastScan
  • Introduced avx512 optimization mode and FAISS_OPT_LEVEL env variable [thanks Alexandr Ghuzva]
  • Added search parameters for IndexRefine::search() and IndexRefineFlat::search()
  • Supported large two-level clustering
  • Added support for Python 3.11 and 3.12
  • Added support for CUDA 12

Changed

  • Used the benchmark to find Pareto optimal indices. Intentionally limited to IVF(Flat|HNSW),PQ|SQ indices
  • Splitted off RQ encoding steps to another file
  • Supported better NaN handling
  • HNSW speedup + Distance 4 points [thanks Alexandr Ghuzva]

Fixed

  • Fixed DeviceVector reallocations in Faiss GPU
  • Used efSearch from params if provided in HNSW search
  • Fixed warp synchronous behavior in Faiss GPU CUDA 12

1.7.4 - 2023-04-12

Added

  • Added big batch IVF search for conducting efficient search with big batches of queries
  • Checkpointing in big batch search support
  • Precomputed centroids support
  • Support for iterable inverted lists for eg. key value stores
  • 64-bit indexing arithmetic support in FAISS GPU
  • IndexIVFShards now handle IVF indexes with a common quantizer
  • Jaccard distance support
  • CodePacker for non-contiguous code layouts
  • Approximate evaluation of top-k distances for ResidualQuantizer and IndexBinaryFlat
  • Added support for 12-bit PQ / IVFPQ fine quantizer decoders for standalone vector codecs (faiss/cppcontrib)
  • Conda packages for osx-arm64 (Apple M1) and linux-aarch64 (ARM64) architectures
  • Support for Python 3.10

Removed

  • CUDA 10 is no longer supported in precompiled packages
  • Removed Python 3.7 support for precompiled packages
  • Removed constraint for using fine quantizer with no greater than 8 bits for IVFPQ, for example, now it is possible to use IVF256,PQ10x12 for a CPU index

Changed

  • Various performance optimizations for PQ / IVFPQ for AVX2 and ARM for training (fused distance+nearest kernel), search (faster kernels for distance_to_code() and scan_list_*()) and vector encoding
  • A magnitude faster CPU code for LSQ/PLSQ training and vector encoding (reworked code)
  • Performance improvements for Hamming Code computations for AVX2 and ARM (reworked code)
  • Improved auto-vectorization support for IP and L2 distance computations (better handling of pragmas)
  • Improved ResidualQuantizer vector encoding (pooling memory allocations, avoid r/w to a temporary buffer)

Fixed

  • HSNW bug fixed which improves the recall rate! Special thanks to zh Wang @hhy3 for this.
  • Faiss GPU IVF large query batch fix
  • Faiss + Torch fixes, re-enable k = 2048
  • Fix the number of distance computations to match max_codes parameter
  • Fix decoding of large fast_scan blocks

1.7.3 - 2022-11-3

Added

  • Added sparse k-means routines and moved the generic kmeans to contrib
  • Added FlatDistanceComputer for all FlatCodes indexes
  • Support for fast accumulation of 4-bit LSQ and RQ
  • Added product additive quantization
  • Support per-query search parameters for many indexes + filtering by ids
  • write_VectorTransform and read_vectorTransform were added to the public API (by @AbdelrahmanElmeniawy)
  • Support for IDMap2 in index_factory by adding "IDMap2" to prefix or suffix of the input String (by @AbdelrahmanElmeniawy)
  • Support for merging all IndexFlatCodes descendants (by @AbdelrahmanElmeniawy)
  • Remove and merge features for IndexFastScan (by @AbdelrahmanElmeniawy)
  • Performance improvements: 1) specialized the AVX2 pieces of code speeding up certain hotspots, 2) specialized kernels for vector codecs (this can be found in faiss/cppcontrib)

Fixed

  • Fixed memory leak in OnDiskInvertedLists::do_mmap when the file is not closed (by @AbdelrahmanElmeniawy)
  • LSH correctly throws error for metric types other than METRIC_L2 (by @AbdelrahmanElmeniawy)

1.7.2 - 2021-12-15

Added

  • Support LSQ on GPU (by @KinglittleQ)
  • Support for exact 1D kmeans (by @KinglittleQ)

1.7.1 - 2021-05-27

Added

  • Support for building C bindings through the FAISS_ENABLE_C_API CMake option.
  • Serializing the indexes with the python pickle module
  • Support for the NNDescent k-NN graph building method (by @KinglittleQ)
  • Support for the NSG graph indexing method (by @KinglittleQ)
  • Residual quantizers: support as codec and unoptimized search
  • Support for 4-bit PQ implementation for ARM (by @vorj, @n-miyamoto-fixstars, @LWisteria, and @matsui528)
  • Implementation of Local Search Quantization (by @KinglittleQ)

Changed

  • The order of xb an xq was different between faiss.knn and faiss.knn_gpu. Also the metric argument was called distance_type.
  • The typed vectors (LongVector, LongLongVector, etc.) of the SWIG interface have been deprecated. They have been replaced with Int32Vector, Int64Vector, etc. (by h-vetinari)

Fixed

  • Fixed a bug causing kNN search functions for IndexBinaryHash and IndexBinaryMultiHash to return results in a random order.
  • Copy constructor of AlignedTable had a bug leading to crashes when cloning IVFPQ indices.

1.7.0 - 2021-01-27

1.6.5 - 2020-11-22

1.6.4 - 2020-10-12

Added

  • Arbitrary dimensions per sub-quantizer now allowed for GpuIndexIVFPQ.
  • Brute-force kNN on GPU (bfKnn) now accepts int32 indices.
  • Nightly conda builds now available (for CPU).
  • Faiss is now supported on Windows.

1.6.3 - 2020-03-24

Added

Changed

  • Replaced obj table in Clustering object: now it is a ClusteringIterationStats structure that contains additional statistics.

Removed

  • Removed support for useFloat16Accumulator for accumulators on GPU (all accumulations are now done in float32, regardless of whether float16 or float32 input data is used).

Fixed

  • Some python3 fixes in benchmarks.
  • Fixed GpuCloner (some fields were not copied, default to no precomputed tables with IndexIVFPQ).
  • Fixed support for new pytorch versions.
  • Serialization bug with alternative distances.
  • Removed test on multiple-of-4 dimensions when switching between blas and AVX implementations.

1.6.2 - 2020-03-10

1.6.1 - 2019-12-04

1.6.0 - 2019-09-24

Added

  • Faiss as a codec: We introduce a new API within Faiss to encode fixed-size vectors into fixed-size codes. The encoding is lossy and the tradeoff between compression and reconstruction accuracy can be adjusted.
  • ScalarQuantizer support for GPU, see gpu/GpuIndexIVFScalarQuantizer.h. This is particularly useful as GPU memory is often less abundant than CPU.
  • Added easy-to-use serialization functions for indexes to byte arrays in Python (faiss.serialize_index, faiss.deserialize_index).
  • The Python KMeans object can be used to use the GPU directly, just add gpu=True to the constuctor see gpu/test/test_gpu_index.py test TestGPUKmeans.

Changed

  • Change in the code layout: many C++ sources are now in subdirectories impl/ and utils/.

1.5.3 - 2019-06-24

Added

Changed

  • Throw python exception for OOM (facebookresearch#758).
  • Make DistanceComputer available for all random access indexes.
  • Gradually moving from long to uint64_t for portability.

Fixed

1.5.2 - 2019-05-28

Added

  • Support for searching several inverted lists in parallel (parallel_mode != 0).
  • Better support for PQ codes where nbit != 8 or 16.
  • IVFSpectralHash implementation: spectral hash codes inside an IVF.
  • 6-bit per component scalar quantizer (4 and 8 bit were already supported).
  • Combinations of inverted lists: HStackInvertedLists and VStackInvertedLists.
  • Configurable number of threads for OnDiskInvertedLists prefetching (including 0=no prefetch).
  • More test and demo code compatible with Python 3 (print with parentheses).

Changed

  • License was changed from BSD+Patents to MIT.
  • Exceptions raised in sub-indexes of IndexShards and IndexReplicas are now propagated.
  • Refactored benchmark code: data loading is now in a single file.

1.5.1 - 2019-04-05

Added

  • MatrixStats object, which reports useful statistics about a dataset.
  • Option to round coordinates during k-means optimization.
  • An alternative option for search in HNSW.
  • Support for range search in IVFScalarQuantizer.
  • Support for direct uint_8 codec in ScalarQuantizer.
  • Better support for PQ code assignment with external index.
  • Support for IMI2x16 (4B virtual centroids).
  • Support for k = 2048 search on GPU (instead of 1024).
  • Support for renaming an ondisk invertedlists.
  • Support for nterrupting computations with interrupt signal (ctrl-C) in python.
  • Simplified build system (with --with-cuda/--with-cuda-arch options).

Changed

  • Moved stats() and imbalance_factor() from IndexIVF to InvertedLists object.
  • Renamed IndexProxy to IndexReplicas.
  • Most CUDA mem alloc failures now throw exceptions instead of terminating on an assertion.
  • Updated example Dockerfile.
  • Conda packages now depend on the cudatoolkit packages, which fixes some interferences with pytorch. Consequentially, faiss-gpu should now be installed by conda install -c pytorch faiss-gpu cudatoolkit=10.0.

1.5.0 - 2018-12-19

Added

  • New GpuIndexBinaryFlat index.
  • New IndexBinaryHNSW index.

1.4.0 - 2018-08-30

Added

  • Automatic tracking of C++ references in Python.
  • Support for non-intel platforms, some functions optimized for ARM.
  • Support for overriding nprobe for concurrent searches.
  • Support for floating-point quantizers in binary indices.

Fixed

  • No more segfaults due to Python's GC.
  • GpuIndexIVFFlat issues for float32 with 64 / 128 dims.
  • Sharding of flat indexes on GPU with index_cpu_to_gpu_multiple.

1.3.0 - 2018-07-10

Added

  • Support for binary indexes (IndexBinaryFlat, IndexBinaryIVF).
  • Support fp16 encoding in scalar quantizer.
  • Support for deduplication in IndexIVFFlat.
  • Support for index serialization.

Fixed

  • MMAP bug for normal indices.
  • Propagation of io_flags in read func.
  • k-selection for CUDA 9.
  • Race condition in OnDiskInvertedLists.

1.2.1 - 2018-02-28

Added

  • Support for on-disk storage of IndexIVF data.
  • C bindings.
  • Extended tutorial to GPU indices.