NVIDIA RAPIDS cuVS is a GPU-accelerated library for vector search and clustering with CUDA-optimized HNSW, IVF, CAGRA, and PQ implementations. Supports batch queries for high QPS, suited for large-scale similarity search in GenAI apps. Achieves up to 12x faster indexing and lower latency vs CPU-only alternatives like FAISS CPU.
Source: GitHub - rapidsai/cuvs
cuVS is an open-source library from RAPIDS for fast, GPU-accelerated vector search and clustering, designed to simplify and accelerate vector similarity search and clustering tasks using state-of-the-art algorithms on NVIDIA GPUs. It is derived from the RAPIDS RAFT library and will become its primary home for approximate nearest neighbors (ANN) and clustering algorithms in late 2024.
cuVS is open-source and free to use under its license.
cuVS is released under an open-source license (see the repository for details).
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