ANNLib: A Development Framework for Efficient Approximate Nearest Neighbor Search
Approximate Nearest Neighbor Search (ANNS) plays a pivotal role in modern deep learning pipelines. Recently, many ANNS systems have been proposed to provide broad, flexible functionalities or achieve high performance. However, it is inherently difficult to achieve both. We propose ANNLib to address this gap. ANNLib is a library that provides a programming framework to achieve high performance and flexible functionalities for ANNS systems, based on popular graph-based ANNS algorithms. We carefully decouple and independently optimize both the algorithm and the data structure components in an ANNS system. In addition, we integrate state-of-the-art algorithms and data structures as modules in...
| Authors | Zheqi Shen, Zijin Wan, Jingbo Su et al. |
|---|---|
| Primary category | cs.LG |
| Published | 20 July 2026 |
| Last updated at source | 18 September 2026 |
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