1 citations · 1 across the 3 of their papers we have counts for
4 papers
Towards the Distributed Large-scale k-NN Graph Construction by Graph Merge
Cheng Zhang, Wan-Lei Zhao, Shihai Xiao +2
In order to support the real-time interaction with LLMs and the instant search or the instant recommendation on social media, it becomes an imminent problem to build a k-NN graph o…
KBest: Efficient Vector Search on Kunpeng CPU
Kaihao Ma, Meiling Wang, Senkevich Oleg +19
Vector search, which returns the vectors most similar to a given query vector from a large vector dataset, underlies many important applications such as search, recommendation, and…
FusionANNS: An Efficient CPU/GPU Cooperative Processing Architecture for Billion-scale Approximate Nearest Neighbor Search
Bing Tian, Haikun Liu, Yuhang Tang +6
Approximate nearest neighbor search (ANNS) has emerged as a crucial component of database and AI infrastructure. Ever-increasing vector datasets pose significant challenges in term…
DiskANN++: Efficient Page-based Search over Isomorphic Mapped Graph Index using Query-sensitivity Entry Vertex
Jiongkang Ni, Xiaoliang Xu, Yuxiang Wang +4
Given a vector dataset and a query vector , graph-based Approximate Nearest Neighbor Search (ANNS) aims to build a graph index and approximately return…