ParlayANN is a library of approximate nearest neighbor search algorithms, along with a set of useful tools for designing such algorithms. It is written in C++ and uses parallel primitives from ParlayLib. Currently it includes implementations of the ANNS algorithms DiskANN, HNSW, HCNNG, and pyNNDescent.
To install, clone the repo and then initiate the ParlayLib submodule:
git submodule init
git submodule updateSee the following documentation for help getting started:
This repository was built for our paper Scaling Graph-Based ANNS Algorithms to Billion-Size Datasets: A Comparative Analsyis. If you use this repository for your own work, please cite us:
@inproceedings{ANNScaling,
author = {Manohar, Magdalen Dobson and Shen, Zheqi and Blelloch, Guy and Dhulipala, Laxman and Gu, Yan and Simhadri, Harsha Vardhan and Sun, Yihan},
title = {ParlayANN: Scalable and Deterministic Parallel Graph-Based Approximate Nearest Neighbor Search Algorithms},
year = {2024},
isbn = {9798400704352},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3627535.3638475},
doi = {10.1145/3627535.3638475},
booktitle = {Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming},
pages = {270–285},
numpages = {16},
keywords = {nearest neighbor search, vector search, parallel algorithms},
location = {Edinburgh, United Kingdom},
series = {PPoPP '24}
}