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v25.06.00

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@raydouglass raydouglass released this 05 Jun 20:15
· 400 commits to main since this release
v25.06.00
2e20f1e

🚨 Breaking Changes

  • [Java] Adding support for prefiltering in CAGRA (#870) @punAhuja

🐛 Bug Fixes

  • Fix failing CAGRA merge google tests for 25.06 (#974) @rhdong
  • Fix for recent NCCL resource update (#968) @viclafargue
  • Revert "Fix kmeans::predict argument order (#915)" (#951) @divyegala
  • IVF-PQ tests: fix segfault when accessing empty lists (#933) @achirkin
  • batch_load_iterator shall copy data located in host memory (#926) @tfeher
  • Fix kmeans::predict argument order (#915) @enp1s0
  • ANN_BENCH: fix the reported core count (#896) @achirkin
  • CUVS_ANN_BENCH_SINGLE_EXE: find the mg library (#890) @achirkin
  • [FIX] Revert negated InnerProduct distance for NN Descent (#859) @jinsolp
  • IVF-PQ tests: fix segfault when accessing empty lists (#838) @achirkin
  • [CuVS-Java] Automate panama bindings generation, Include IVF_PQ parameters in CAGRA index parameters and other changes (#831) @narangvivek10
  • Ann-bench: fix unsafe lazy blobs (#828) @achirkin
  • Fix test_brute_force conversion (#821) @lowener
  • [FEA] New algos and updates/corrections to Faiss cuvs-bench (#677) @tarang-jain

📖 Documentation

🚀 New Features

🛠️ Improvements

  • Update score calculation for CAGRA-Q instance selection (#938) @enp1s0
  • [FEA] Use Native Brute Force for Sparse Pairwise KNN (#927) @tarang-jain
  • use 'rapids-init-pip' in wheel CI, other CI changes (#917) @jameslamb
  • ANN_BENCH: Avoid repeated calls to raft::get_device_for_address in CAGRA search (#908) @achirkin
  • [Java] New off-heap Dataset support for CAGRA and Bruteforce (#902) @chatman
  • Finish CUDA 12.9 migration and use branch-25.06 workflows (#901) @bdice
  • Update to clang 20 (#898) @bdice
  • get Java artifacts from GitHub Actions artifact store (#893) @jameslamb
  • Quote head_rev in conda recipes (#892) @bdice
  • [Java] Exposing merge API for multiple CAGRA indices (#891) @punAhuja
  • Expose ivf-flat centers to python/c (#888) @benfred
  • CUDA 12.9 use updated compression flags (#887) @robertmaynard
  • Expose ivf-pq centers to python/c (#881) @benfred
  • Accept host inputs in python for ivf-pq build and extend (#880) @benfred
  • Add tiered_index support (#879) @benfred
  • Exclude librmm.so from auditwheel (#878) @bdice
  • update.version.sh: remove broken reference, skip most CI on PRs that only modify update-version.sh (#875) @jameslamb
  • Add support for Python 3.13 (#874) @gforsyth
  • chore: lower wheel size threshold (#872) @gforsyth
  • [Java] Adding support for prefiltering in CAGRA (#870) @punAhuja
  • Change snmg index to use updated multi gpu resource API (#869) @jinsolp
  • run shellcheck on all files, other small pre-commit updates (#865) @jameslamb
  • Fix IVF PQ build metric for CAGRA (#862) @lowener
  • ANN_BENCH: Expose parallel_mode parameter of FAISS CPU IVF implementation (#861) @achirkin
  • Specify matplotlib version (#839) @benfred
  • Use random tmp names for index files in tests (#837) @achirkin
  • Download build artifacts from Github for CI (#834) @VenkateshJaya
  • Add NN-Descent return_distances functionality to python/C (#833) @benfred
  • Optimize hnsw::from_cagra<GPU> (#826) @achirkin
  • Use vendored RAPIDS.cmake in example code. (#824) @bdice
  • refactor(rattler): enable strict channel priority for builds (#823) @gforsyth
  • Reduce device memory usage for CAGRA's graph optimization process (2-hop detour counting) (#822) @anaruse
  • [cuvs_bench] distinguish search label from build label in data_export.py (#818) @jiangyinzuo
  • Vendor RAPIDS.cmake (#816) @bdice
  • Update libcuvs libraft ver to 25.06 in conda env (#808) @jinsolp
  • Moving NN Descent class and struct declarations to nn_descent_gnnd.hpp (#803) @jinsolp
  • Remove @rapidsai/cuvs-build-codeowners (#783) @KyleFromNVIDIA
  • Moving wheel builds to specified location and uploading build artifacts to Github (#777) @VenkateshJaya
  • Remove unused raft cagra header in add_nodes.cuh (#741) @jiangyinzuo
  • Expose kmeans to python (#729) @benfred
  • Update cuvs to properly create a NCCL::NCCL target (#720) @robertmaynard
  • Optimize euclidean distance in host refine phase (#689) @anstellaire
  • Moving MG functions into unified API + raft::device_resources_snmg as device resource type for MG functions (#454) @viclafargue
  • Moving random ball cover (#218) @cjnolet