ParlayANN
ParlayANN is a scalable and deterministic parallel graph-based approximate nearest neighbor (ANN) search library. It provides parallel algorithms and implementations for high-dimensional vector similarity search, suitable as a core search component in large-scale vector database and retrieval systems.
About this tool
ParlayANN
Category: SDKs & Libraries
Website: https://github.com/cmuparlay/ParlayANN
License: See LICENSE file in repository
Description
ParlayANN is a C++ library of scalable, deterministic, parallel graph-based approximate nearest neighbor (ANN) search algorithms for high-dimensional vector similarity search. It is designed for use as a core search component in large-scale vector databases and retrieval systems, and builds on parallel primitives from ParlayLib.
Features
- Multiple ANN algorithms implemented
- DiskANN
- HNSW
- HCNNG
- pyNNDescent
- Graph-based indices suitable for high-dimensional ANN search
- Parallel execution using ParlayLib primitives for scalability
- Range search support via algorithms from the paper Range Retrieval with Graph-Based Indices
- Tools for algorithm design: utilities and data tools to help design and experiment with ANN algorithms
- C++ implementation for performance and low-level control
- Python directory present in the repo, indicating Python-related bindings or tooling
- Build system support
- CMake configuration (
CMakeLists.txt) - Bazel configuration (
WORKSPACE,.bazelrc)
- CMake configuration (
Technology Stack
- Language: C++ (with associated Python directory)
- Parallel library: ParlayLib
- Focus: Graph-based approximate nearest neighbor and range search in high dimensions
Use Cases
- Core similarity search component in vector databases
- Large-scale vector retrieval and recommendation systems
- Research and experimentation on graph-based ANN algorithms
Pricing
ParlayANN is an open-source library. No pricing plans are specified; usage terms are governed by the license provided in the repository (LICENSE).
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