Work

Achieving Low-Latency Graph-Based Vector Search via Aligning Best-First Search Algorithm with SSD

Year: 2026

Type: article

Abstract: We propose PipeANN , an on-disk graph-based approximate nearest neighbor search (ANNS) system, which significantly bridges the latency gap with in-memory ones. We achieve this by aligning the best-first search algorithm with SSD characteristics, avoiding strict compute-I/O order across search steps. Experiments show that PipeANN has 1.14×–2.02× search latency compared to in-memory Vamana, and 35.0% of the latency of on-disk DiskANN in billion-scale datasets, without sacrificing search accuracy. PipeANN is open-source at https://github.com/thustorage/PipeANN .

Source: ACM Transactions on Storage

DOI: 10.1145/3793926

Authors: Hao Guo, Youyou Lu

Institution: Tsinghua University

Language: English

Topic: Advanced Image and Video Retrieval Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Natural Science Foundation of China, National Key Research and Development Program of China

Awards: G4440035852, G5944769046