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Releases: NVIDIA/cuvs

v26.08.01

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@gforsyth gforsyth released this 06 Aug 17:52
25b1be4

Full Changelog: v26.08.00...v26.08.01

v26.08.00

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@gforsyth gforsyth released this 05 Aug 19:38
6ba2ce2

What's Changed

🚨 Breaking Changes

🐛 Bug Fixes

  • [CI nightly] Temporarily disable conda-python-tests codecov reporting by @aamijar in #2274
  • Exclude SPDX copyright lines from .clang-format by @achirkin in #2275
  • Fix FastIntDiv tparam by @aamijar in #2278
  • CAGRA: fix concurrent initialization and usage of dataset descriptor by @achirkin in #2237
  • Revert "FIX: disable warpspeed scan (#2062)" by @bdice in #2074
  • Predict IVF-PQ FP16 overflow and auto-switch to FP32 by @huuanhhuyn in #2246
  • Update .clang-format to fix copyright and style check by @HowardHuang1 in #2304
  • Fix batched silhouette score stream ordering by @csadorf in #2316
  • fix(pre-commit): normalize SPDX handling by @bdice in #2318
  • Remove fragile explicit import that breaks with jextract/CUDA changes by @imotov in #2124
  • Remove trailing new lines from GTest names by @robertmaynard in #2312
  • Update Comparison Branch for ABI Stability Git Workflow by @tarang-jain in #2331
  • CAGRA ACE build: avoid rounding down graph degree during sub-index build by @achirkin in #2335
  • [BUG] Fix CAGRA search recall with a graph built by NN Descent by @enp1s0 in #819
  • Fix IVF extend list resize bug by @qwertyforce in #2297
  • Use batched unfused 1-NN for KMeans on Blackwell by @viclafargue in #2346
  • Fix prefilter bitmap host buffer under-allocation in Java bindings by @imotov in #2375
  • Fix incorrect distances tensor type in cuvsCagraSearch by @imotov in #2372

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🚀 New Features

🛠️ Improvements

New Contributors

Full Changelog: v26.08.00a...v26.08.00

v26.06.00

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@jolorunyomi jolorunyomi released this 04 Jun 00:21
2bd7cd7

What's Changed

🚨 Breaking Changes

🐛 Bug Fixes

📖 Documentation

🚀 New Features

🛠️ Improvements

New Contributors

Full Changelog: v26.06.00a...v26.06.00

v26.04.00

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@AyodeAwe AyodeAwe released this 08 Apr 19:23
60b19a0

What's Changed

🚨 Breaking Changes

  • Use HNSW GPU Hierarchy by Default by @julianmi in #1617
  • Backport "Default to static linking of libcudart" by @KyleFromNVIDIA in #1918
  • enforce a floor on libnvjitlink, build wheels with CUDA 13.0.x, test wheels against mix of CTK versions by @jameslamb in #1862

🐛 Bug Fixes

📖 Documentation

🚀 New Features

🛠️ Improvements

New Contributors

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v26.02.00

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@AyodeAwe AyodeAwe released this 04 Feb 21:46
v26.02.00
a2f5a8b

What's Changed

🚨 Breaking Changes

🐛 Bug Fixes

📖 Documentation

🚀 New Features

🛠️ Improvements

New Contributors

Full Changelog: v26.02.00a...v26.02.00

v25.12.00

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@AyodeAwe AyodeAwe released this 11 Dec 00:51
v25.12.00
fc27938

What's Changed

🚨 Breaking Changes

🐛 Bug Fixes

📖 Documentation

🚀 New Features

🛠️ Improvements

New Contributors

Full Changelog: v25.12.00a...v25.12.00

v25.10.00

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@AyodeAwe AyodeAwe released this 08 Oct 19:39

🚨 Breaking Changes

🐛 Bug Fixes

📖 Documentation

🚀 New Features

🛠️ Improvements

[NIGHTLY] v25.12.00

[NIGHTLY] v25.12.00 Pre-release
Pre-release

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@rapids-bot rapids-bot released this 02 Oct 16:47

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🚨 Breaking Changes

🐛 Bug Fixes

🚀 New Features

🛠️ Improvements

v25.08.00

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@AyodeAwe AyodeAwe released this 06 Aug 19:25
9ce11a0

🚨 Breaking Changes

🐛 Bug Fixes

📖 Documentation

🚀 New Features

🛠️ Improvements

  • Check shape is initialized in cuvsMatrixSliceRows (#1193) @benfred
  • Add error checking for our C example code (#1171) @benfred
  • Removing all references to CUDA 11 from codebase (#1150) @cjnolet
  • [Java]Fixed TieredIndexParams creation/destruction, calling cuvsTieredIndexParamsCreate (#1147) @punAhuja
  • Fix update-version (#1135) @AyodeAwe
  • Reducing binary size in ivf_pq by deduplicating kernels (#1130) @jinsolp
  • fix(docker): use versioned -latest tag for all rapidsai images (#1129) @gforsyth
  • SCaNN Index build (#1120) @rmaschal
  • [Java] Extend Dataset to work as an output data container (#1111) @ldematte
  • [Java] Fix HNSW params allocation (#1110) @ldematte
  • [Java] Fix CAGRA params allocation (#1109) @ldematte
  • [Java] Fix POM (#1106) @ldematte
  • Enforce java codeowners for managing contents of java/ (#1103) @cjnolet
  • Reduce binary size of refine functions (#1095) @tfeher
  • [Java] Introduce scoped resource access (#1089) @ldematte
  • Expose graph and dataset accessors for CAGRA to C/Python (#1086) @benfred
  • Add warning for unused GPU when n_clusters < n_ranks in batch all_neighbors (#1072) @jinsolp
  • [Java] Tidy up MemorySegments lifecycle (#1069) @ldematte
  • [Java] Refactor SearchResults implementation classes (#1067) @ldematte
  • Use CUDA 12.9 in Conda, Devcontainers, Spark, GHA, etc. (#1063) @jakirkham
  • Exporting changed graph_build_params namespace into all_neighbors (#1060) @jinsolp
  • hnsw::from_cagra: avoid allocating the graph twice (#1057) @achirkin
  • Improve memory efficiency for returning NN Descent distances (#1053) @jinsolp
  • Deprecation notice for batching code specific to NN Descent (#1052) @jinsolp
  • Remove nvidia and dask channels (#1050) @vyasr
  • [Java] Enforce Java code format standard (#1049) @narangvivek10
  • Make rust publish run after conda upload (#1047) @AyodeAwe
  • refactor(cuda11): remove cuda11-only conda channels, cleanup docs (#1046) @gforsyth
  • [Review][Java] Fix random segabort/segfault/double free problems (#1045) @ldematte
  • [Java] Add Dataset based on MemorySegment (#1034) @ldematte
  • [Java] Add Java API benchmarks (#1033) @ldematte
  • fix(cli): Add validation for search-mode parameter (#1026) @mayani-nv
  • [Java] Encapsulate on-heap float arrays into Dataset (#1024) @ldematte
  • refactor(shellcheck): fix all remaining warnings/errors (#1019) @gforsyth
  • Instantiate only specific RAFT linewise kernels (#1018) @aamijar
  • Update nightly CI check to allow 30 days of failing nightly build. (#1008) @cjnolet
  • [Java] Using functions for mapping (#1007) @ldematte
  • [REVIEW][Java] Refactor CagraBuildAndSearchIT to explicitly express different execution modes (#1006) @ldematte
  • [REVIEW][Java] Add jextract artifacts to gitignore (#1005) @ldematte
  • Remove pytest pin (#998) @vyasr
  • [java] Utility function for cudaMemcpy (#983) @mythrocks
  • [java] Copy pom.xml to target/ on build (#981) @mythrocks
  • Remove CUDA 11 from dependencies.yaml (#962) @KyleFromNVIDIA
  • refactor(rattler): remove cuda11 options and general cleanup (#961) @gforsyth
  • Remove CUDA 11 devcontainers and update CI scripts (#960) @bdice
  • Common knn graph build params (#949) @jinsolp
  • stop uploading packages to downloads.rapids.ai (#940) @jameslamb
  • Instantiate only specific RAFT reduction kernels (#925) @divyegala
  • [Java] Replace the C wrapper layer with the Panama API-based Java implementation (#916) @narangvivek10
  • Forward-merge branch-25.06 into branch-25.08 (#909) @gforsyth
  • Forward-merge branch-25.06 into branch-25.08 (#897) @gforsyth
  • Serialize Vamana index with SSD sector alignment per MSFT DiskANN format, generate quantized dataset for integration with DiskANN (#846) @jamxia155
  • Add mean and median threshold modes to binary quantization (#716) @enp1s0

v25.06.01

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@AyodeAwe AyodeAwe released this 24 Jun 16:02
27b7272

🚨 Breaking Changes

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

🐛 Bug Fixes

📖 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