Memory-bounded GPU acceleration for graph-based approximate nearest neighbor search.
# Install development tools
sudo dnf install @'Development Tools'
# Install additional dependencies
sudo dnf install epel-release
sudo dnf config-manager --set-enabled crb
sudo dnf install cmake git swig lapack lapack-devel
# Enable NVIDIA repository
sudo dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel9/x86_64/cuda-rhel9.repo
# Install CUDA
sudo dnf clean all
sudo dnf -y install cuda-toolkit-11-8
sudo dnf module install nvidia-driver:latest-dkms
# Set environment variables (add to ~/.bashrc):
export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
# The code is built on top of LibTorch
conda create -n pytorch python=3.10 && conda activate pytorch
conda install pytorch=2.1.2 torchvision torchaudio pytorch-cuda=11.8 numpy -c pytorch -c nvidia
# Download source
git clone https://github.com/facebookresearch/faiss/archive/refs/tags/v1.8.0.tar.gz
tar -xvf v1.8.0.tar.gz && cd faiss-*
# Build faiss
mkdir build && cd build
cmake .. -DFAISS_OPT_LEVEL='avx2' \
-DFAISS_ENABLE_GPU=OFF \
-DFAISS_ENABLE_PYTHON=ON \
-DCMAKE_BUILD_TYPE=Release
# Install
cd faiss/python && python3 ./setup.py install
cd pilot_ann_src
python3 ./setup.py develop
- Expected directory structure:
.datasets/
├── deep-1m/
├── deep-100m/
└── laion-100m/
# Using 16 CPUs
export OMP_THREAD_LIMIT=16
# Run benchmark
python3 script/bench_1.py --dataset='laion-1m' --sample_ratio=0.25 --d_principle=128
python3 script/bench_1.py --dataset='laion-100m' --sample_ratio=0.25 --d_principle=128
- --top_k: Set
k(any int <= 100, default 10) - --dataset: Choose dataset (deep-1m, text2img-1m, wiki-1m, laion-1m)
- --sample_ratio: Set sampling ratio (any float in (0.0, 1.0])
- --d_principle: Set SVD reduction dimension (any int, prefer numbers divisible by 32)
- --algorithm: Choose graph angorithm (hnsw, nsg)
- --router: Entry selection method (random32, random64, router32x32, router64x64, router means FES)
- --n_queries: Set number of queries to process (default 1024)
Benchmark Results
- Example output
[hnsw] dataset: laion-1m, d_model: 768
svd 128
build nsw
sampling 0.25
[INFO] building entry
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[INFO] creating bitmask_pool
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search-pilot: recall=0.904, duration=15.627ms
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search-pilot: recall=0.939, duration=24.763ms
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search-pilot: recall=0.948, duration=32.539ms
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search-pilot: recall=0.956, duration=40.757ms
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search-pilot: recall=0.964, duration=55.374ms
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search-pilot: recall=0.968, duration=69.943ms
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search-pilot: recall=0.971, duration=98.985ms
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faiss: recall=0.832, duration=46.139ms
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faiss: recall=0.903, duration=65.952ms
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faiss: recall=0.927, duration=84.055ms
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faiss: recall=0.941, duration=102.547ms
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faiss: recall=0.960, duration=176.475ms
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faiss: recall=0.973, duration=329.534ms
search-pilot {'recall': 0.9042089843749965, 'timing': 15.62661695000429, 'n_neighbors': 32, 'ef_search': 16}
search-pilot {'recall': 0.9386181640624971, 'timing': 24.763099350008133, 'n_neighbors': 32, 'ef_search': 32}
search-pilot {'recall': 0.9479541015624975, 'timing': 32.53943175001268, 'n_neighbors': 32, 'ef_search': 48}
search-pilot {'recall': 0.9558251953124977, 'timing': 40.75729169999818, 'n_neighbors': 32, 'ef_search': 64}
search-pilot {'recall': 0.9635205078124978, 'timing': 55.373822949991336, 'n_neighbors': 32, 'ef_search': 96}
search-pilot {'recall': 0.9676708984374981, 'timing': 69.94290830000409, 'n_neighbors': 32, 'ef_search': 128}
search-pilot {'recall': 0.9708789062499983, 'timing': 98.98512790001064, 'n_neighbors': 32, 'ef_search': 192}
search-pilot {'recall': 0.9735009765624982, 'timing': 125.94395004999228, 'n_neighbors': 32, 'ef_search': 256}
faiss {'recall': 0.8318408203124973, 'timing': 46.139192449993516, 'n_neighbors': 32, 'ef_search': 16}
faiss {'recall': 0.9028222656249973, 'timing': 65.95181419999108, 'n_neighbors': 32, 'ef_search': 32}
faiss {'recall': 0.9267089843749978, 'timing': 84.05481609999015, 'n_neighbors': 32, 'ef_search': 48}
faiss {'recall': 0.9410009765624979, 'timing': 102.54711749997796, 'n_neighbors': 32, 'ef_search': 64}
faiss {'recall': 0.953413085937498, 'timing': 138.67827450001187, 'n_neighbors': 32, 'ef_search': 96}
faiss {'recall': 0.9601367187499985, 'timing': 176.47515465000652, 'n_neighbors': 32, 'ef_search': 128}
faiss {'recall': 0.9666748046874986, 'timing': 250.98584330000904, 'n_neighbors': 32, 'ef_search': 192}
faiss {'recall': 0.9726123046874987, 'timing': 329.5344065999984, 'n_neighbors': 32, 'ef_search': 256}