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About this paper
Alexander Ponomarenko
A unified framework treats HNSW index consolidation as a graph-reconstruction task rather than repeated point insertion, and compares three merge strategies: Naive Graph Merge, Intra Graph Traversal Merge, and Cross Graph Traversal Merge. On SIFT1M, the locality-aware IGTM method used about 70% fewer distance computations than exhaustive merging or simple insertion, and about 20% fewer than CGTM, while retaining comparable recall.
Key insights
- Reusing candidate sets while processing spatially nearby vertices can replace many expensive hierarchical searches with cheaper local traversals.
- Allowing traversal to switch between both input graphs does not necessarily improve efficiency: CGTM reduces search work versus naive merging, but its dual-graph bookkeeping is more costly than IGTM’s one-graph-at-a-time traversal.
- Merge-time computation is the main point of separation among the methods; query-time distance costs on the resulting graphs are broadly similar for fixed search parameters.
Summary by alphaXiv.
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