SVFusion: A CPU-GPU Co-Processing Architecture for Large-Scale Real-Time Vector Search
Summary: SVFusion co-designs a hierarchical GPU–CPU–disk ANN index for high-throughput search with online updates, using workload-aware GPU caching, CUDA streams, adaptive resource management, and concurrency control. It delivers up to 20.9× higher throughput and 50.7× lower latency while preserving recall.
(summarized by gpt-5.6-luna on Jul 24 2026)
5.
Lidan Shou
(Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security; Zhejiang University)
6.
Ke Chen
(Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security; Zhejiang University)
7.
Gang Chen
(Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security; Zhejiang University)
BibTeX Citation
@article{peng_vldb26,
title = {{SVFusion: A CPU-GPU Co-Processing Architecture for Large-Scale Real-Time Vector Search}},
author = {Peng, Yuchen and Yang, Dingyu and Xie, Zhongle and Sun, Ji and Shou, Lidan and Chen, Ke and Chen, Gang},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {5},
pages = {1074--1087},
doi = {10.14778/3796195.3796216},
url = {https://doi.org/10.14778/3796195.3796216},
year = {2026}
}
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