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  • version 0.3.0:

    The distances implementation is now in a separate crate anndsits. Using hnsw_rs::prelude:::* should make the change transparent.

    The mmap implentation makes it possible to use the coreset crate to compute coreset and clusters of data stored in hnsw dumps.

  • version 0.2.1:

    when using mmap, the points less frequently used (points in lower layers) are preferentially mmap-ed while upper layers are preferentially explcitly read from file.

    Hnswio is now Sync.

    feature stdsimd, based on std::simd, runs with nightly on Hamming with u32,u64 and DisL1,DistL2, DistDot with f32

  • The version 0.2 introduces

    1. possibility to use mmap on the data file storing the vectors represented in the hnsw structure. This is mostly usefule for large vectors, where data needs more space than the graph part. As a consequence the format of this file changed. Old format can be read but new dumps will be in the new format.
      In case of mmap usage, a dump after inserting new elements must ensure that the old file is not overwritten, so a unique file name is generated if necessary. See documentation of module Hnswio

    2. the filtering trait

  • Upgrade of many dependencies. Change from simple_logger to env_logger. The logger is initialized one for all in file src/lib.rs and cannot be intialized twice. The level of log can be modulated by the RUST_LOG env variable on a module basis or switched off. See the env_logger crate doc.

  • A rust crate edlib_rs provides an interface to the excellent edlib C++ library (Cf edlib) can be found at edlib_rs or on crate.io. It can be used to define a user adhoc distance on &[u8] with normal, prefix or infix mode (which is useful in genomics alignment).

  • The library do not depend anymore on hdf5 and ndarray. They are dev-dependancies needed for examples, this simplify compatibility issues.

  • Added insertion methods for slices for easier use with the ndarray crate.

  • simd/avx2 requires now the feature "simdeez_f". So by default the crate can compile on M1 chip and transitions to std::simd.

  • Added DistPtr and possiblity to dump/reload with this distance type. (See load_hnsw_with_dist function)

  • Implementation of Hamming for f64 exclusively in the context SuperMinHash in crate probminhash