https://github.com/harsha-simhadri/big-ann-benchmarks
Framework for evaluating ANNS algorithms on billion scale datasets.
https://github.com/harsha-simhadri/big-ann-benchmarks
approximate-nearest-neighbor-search information-retrival
Last synced: about 1 month ago
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Framework for evaluating ANNS algorithms on billion scale datasets.
- Host: GitHub
- URL: https://github.com/harsha-simhadri/big-ann-benchmarks
- Owner: harsha-simhadri
- License: mit
- Created: 2021-06-18T00:14:02.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2025-02-18T19:34:20.000Z (4 months ago)
- Last Synced: 2025-03-31T19:09:36.435Z (3 months ago)
- Topics: approximate-nearest-neighbor-search, information-retrival
- Language: Jupyter Notebook
- Homepage: https://big-ann-benchmarks.com
- Size: 123 MB
- Stars: 368
- Watchers: 18
- Forks: 128
- Open Issues: 40
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Big ANN Benchmarks
## Datasets
See for details on the different datasets.
## NeurIPS 2023 competition: Practical Vector Search
Please see [this readme](./neurips23/README.md) for a guide to the NeurIPS 23 competition.
## NeurIPS 2021 competition: Billion-Scale ANN
Please see [this readme](./neurips21/README.md) for a guide of running billion-scale benchmarks and a summary of the results from the NeurIPS 21 competition.
# Credits
This project is a version of [ann-benchmarks](https://github.com/erikbern/ann-benchmarks) by [Erik Bernhardsson](https://erikbern.com/) and contributors targeting evaluation of algorithms and hardware for newer billion-scale datasets and practical variants of nearest neighbor search.