4 papers
DISTRIBUTEDANN: Efficient Scaling of a Single DISKANN Graph Across Thousands of Computers
Philip Adams, Menghao Li, Shi Zhang +6
We present DISTRIBUTEDANN, a distributed vector search service that makes it possible to search over a single 50 billion vector graph index spread across over a thousand machines t…
Cost-Effective, Low Latency Vector Search with Azure Cosmos DB
Nitish Upreti, Harsha Vardhan Simhadri, Hari Sudan Sundar +33
Vector indexing enables semantic search over diverse corpora and has become an important interface to databases for both users and AI agents. Efficient vector search requires deep…
BANG: Billion-Scale Approximate Nearest Neighbor Search using a Single GPU
Karthik V., Saim Khan, Somesh Singh +2
Approximate Nearest Neighbour Search (ANNS) is a subroutine in algorithms routinely employed in information retrieval, pattern recognition, data mining, image processing, and beyon…
In-Place Updates of a Graph Index for Streaming Approximate Nearest Neighbor Search
Haike Xu, Magdalen Dobson Manohar, Philip A. Bernstein +3
Indices for approximate nearest neighbor search (ANNS) are a basic component for information retrieval and widely used in database, search, recommendation and RAG systems. In these…