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mnorris11mnorris11
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Merge branch 'main' into hnsw-optim
2 parents 64e2d6d + fd3403e commit d89ae54

36 files changed

Lines changed: 951 additions & 423 deletions

‎.github/actions/build_cmake/action.yml‎

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@@ -73,10 +73,10 @@ runs:
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:
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# regular CUDA for GPU builds
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elif [ "${{ inputs.gpu }}" = "ON" ] && [ "${{ inputs.cuvs }}" = "OFF" ]; then
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conda install -y -q cuda-libraries-dev=12.6 cuda-nvcc=12.6 cuda-nvtx=12.6 cuda-cupti=12.6 cuda-cudart-dev=12.6 gxx_linux-64=12.4 -c "nvidia/label/cuda-12.6"
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conda install -y -q cuda-libraries-dev=13.2 cuda-nvcc=13.2 cuda-nvtx=13.2 cuda-cupti=13.2 cuda-cudart-dev=13.2 gxx_linux-64=14.2 -c "nvidia/label/cuda-13.2"
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# and CUDA from cuVS channel for cuVS builds
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elif [ "${{ inputs.cuvs }}" = "ON" ]; then
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conda install -y -q libcuvs=26.02 'cuda-version=12.9' sysroot_linux-64=2.34 -c rapidsai -c rapidsai-nightly -c conda-forge
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conda install -y -q libcuvs=26.02 'cuda-version=13.2' sysroot_linux-64=2.34 -c rapidsai -c rapidsai-nightly -c conda-forge
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# Clean index cache to prevent sqlite3 "database is locked" errors
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# from conda-libmamba-solver's shards cache between consecutive installs.
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# See: https://github.com/conda/conda-libmamba-solver/issues/667
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: # skip torch install via conda, we need to install via pip to get
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# ROCm-enabled version until it's supported in conda by PyTorch
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elif [ "${{ inputs.gpu }}" = "ON" ]; then
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conda install -y -q "pytorch>=2.7" "pytorch-gpu>=2.7" -c pytorch -c "nvidia/label/12.9"
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# PyTorch deprecated its official Anaconda channel (pytorch/pytorch#138506),
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# so we install via pip for CUDA builds. --break-system-packages is needed
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# because the CI runner's Python is PEP 668 externally-managed.
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pip install "torch>=2.7" --break-system-packages --index-url https://download.pytorch.org/whl/cu132
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else
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# TestLowLevelIVF.IVFRQ hangs on pytorch>=2.7, so left it as <2.5 for now.
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conda install -y -q "pytorch<2.5" -c pytorch

‎.github/workflows/build-pull-request.yml‎

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@@ -277,10 +277,10 @@ jobs:
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- name: Build and Package (conda)
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uses: ./.github/actions/build_conda
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linux-x86_64-GPU-conda:
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name: Linux x86_64 GPU (conda, CUDA 12.6)
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name: Linux x86_64 GPU (conda, CUDA 13.2)
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runs-on: 4-core-ubuntu-gpu-t4
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env:
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CUDA_ARCHS: "70-real;72-real;75-real;80;86-real"
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CUDA_ARCHS: "75-real;80;86-real;90;100;120"
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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- name: Build and Package (conda)
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uses: ./.github/actions/build_conda
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with:
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cuda: "12.6"
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cuda: "13.2"
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linux-x86_64-svs:
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name: Linux x86_64 w/ SVS (cmake)
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needs: linux-x86_64-cmake

‎.github/workflows/build-release.yml‎

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ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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with:
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label: main
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linux-x86_64-GPU-packages-CUDA-12-4-0:
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name: Linux x86_64 GPU packages (CUDA 12.6)
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linux-x86_64-GPU-packages-CUDA-13-2-0:
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name: Linux x86_64 GPU packages (CUDA 13.2)
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runs-on: 4-core-ubuntu-gpu-t4
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env:
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CUDA_ARCHS: "70-real;72-real;75-real;80;86-real"
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CUDA_ARCHS: "75-real;80;86-real;90;100;120"
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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with:
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label: main
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cuda: "12.6"
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linux-x86_64-GPU-CUVS-packages-CUDA12-4-0:
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name: Linux x86_64 GPU w/ cuVS packages (CUDA 12.6)
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cuda: "13.2"
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linux-x86_64-GPU-CUVS-packages-CUDA13-2-0:
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name: Linux x86_64 GPU w/ cuVS packages (CUDA 13.2)
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runs-on: 4-core-ubuntu-gpu-t4
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env:
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CUDA_ARCHS: "70-real;72-real;75-real;80;86-real"
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CUDA_ARCHS: "75-real;80;86-real;90;100;120"
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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with:
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label: main
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cuvs: "ON"
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cuda: "12.6"
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cuda: "13.2"
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windows-x86_64-packages:
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name: Windows x86_64 packages
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runs-on: windows-2022

‎.github/workflows/index-io-backward-compatibility.yml‎

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eval "$(conda shell.bash hook)"
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conda create -n faiss_conda_read -y python=3.12
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conda activate faiss_conda_read
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conda install -y -c pytorch -c conda-forge faiss-cpu=1.14.1 "mkl>=2024.2.2,<2026"
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conda install -y -c pytorch -c conda-forge faiss-cpu=1.14.2 "mkl>=2024.2.2,<2026"
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conda list
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- name: Run Conda reader (read Faiss index and verify)
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eval "$(conda shell.bash hook)"
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conda create -n faiss_conda_write -y python=3.12
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conda activate faiss_conda_write
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conda install -y -c pytorch -c conda-forge faiss-cpu=1.14.1 "mkl>=2024.2.2,<2026"
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conda install -y -c pytorch -c conda-forge faiss-cpu=1.14.2 "mkl>=2024.2.2,<2026"
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conda list
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- name: Create shared data directory

‎.github/workflows/nightly.yml‎

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ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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with:
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label: nightly
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linux-x86_64-GPU-CUDA-12-6-nightly:
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name: Linux x86_64 GPU nightlies (CUDA 12.6)
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linux-x86_64-GPU-CUDA-13-2-nightly:
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name: Linux x86_64 GPU nightlies (CUDA 13.2)
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runs-on: 4-core-ubuntu-gpu-t4
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env:
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CUDA_ARCHS: "70-real;72-real;75-real;80;86-real"
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CUDA_ARCHS: "75-real;80;86-real;90;100;120"
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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with:
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label: nightly
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cuda: "12.6"
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# TODO: re-enable when we have a newer machine in CI that can run CUDA 13.2
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# linux-x86_64-GPU-CUVS-CUDA13-2-0-nightly:
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# name: Linux x86_64 GPU w/ cuVS nightlies (CUDA 13.2)
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# runs-on: 4-core-ubuntu-gpu-t4
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# env:
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# CUDA_ARCHS: "75-real;80;86-real;90;100"
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# steps:
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# - name: Checkout
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# uses: actions/checkout@v4
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# with:
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# fetch-depth: 0
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# fetch-tags: true
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# - uses: ./.github/actions/build_conda
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# env:
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# ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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# with:
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# label: nightly
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# cuvs: "ON"
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# cuda: "13.2"
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cuda: "13.2"
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linux-x86_64-GPU-CUVS-CUDA13-2-0-nightly:
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name: Linux x86_64 GPU w/ cuVS nightlies (CUDA 13.2)
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runs-on: 4-core-ubuntu-gpu-t4
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env:
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CUDA_ARCHS: "75-real;80;86-real;90;100;120"
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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with:
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fetch-depth: 0
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fetch-tags: true
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- uses: ./.github/actions/build_conda
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env:
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ANACONDA_API_TOKEN: ${{ secrets.ANACONDA_API_TOKEN }}
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with:
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label: nightly
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cuvs: "ON"
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cuda: "13.2"
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windows-x86_64-nightly:
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name: Windows x86_64 nightlies
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runs-on: windows-2022

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