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arXiv · 2605.17992

PipeANN-Filter: An Efficient Filtered Vector Search System on SSD

Hao Guo·Jiwu Shu·Youyou Lu
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Abstract

We propose PipeANN-Filter, an efficient filtered vector search system on SSD. Unlike existing systems that explore only valid vectors (i.e., those satisfying the attribute constraints) during search, PipeANN-Filter explores a superset of valid vectors, and performs attribute verification after getting the top-k closest result vectors. This allows PipeANN-Filter to leverage probabilistic data structures (e.g., Bloom filters) to identify the superset, trading off a small number of false-positive vector explorations for a massive reduction in SSD I/O for attribute reading. Evaluations show that PipeANN-Filter improves search latency and throughput compared to state-of-the-art systems. PipeANN-Filter is open-source at https://github.com/thustorage/PipeANN

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Hao Guo, Jiwu Shu, Youyou Lu. 2026-05-18. PipeANN-Filter: An Efficient Filtered Vector Search System on SSD. https://arxiv.org/abs/2605.17992

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