ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
Summary: ParChain parallelizes nearest-neighbor-chain HAC, enabling concurrent merges for complete, average, and Ward linkage with linear rather than quadratic memory. Range-query and distance-caching optimizations yield major speedups and scale to tens of millions of points. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Shangdi Yu (Massachusetts Institute of Technology)
- 2. Yiqiu Wang (Massachusetts Institute of Technology)
- 3. Yan Gu (University of California Riverside)
- 4. Laxman Dhulipala (Massachusetts Institute of Technology)
- 5. Julian Shun (Massachusetts Institute of Technology)
BibTeX Citation
@article{yu_vldb22,
title = {{ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain}},
author = {Yu, Shangdi and Wang, Yiqiu and Gu, Yan and Dhulipala, Laxman and Shun, Julian},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {2},
pages = {285--298},
doi = {10.14778/3489496.3489509},
url = {https://doi.org/10.14778/3489496.3489509},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,816 | TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs | 2023 | SIGMOD | 5.214913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,219 | Twister Tries: Approximate Hierarchical Agglomerative Clustering for Average Distance in Linear Time | 2015 | SIGMOD | 5.9425753e-05 |
| 7,862 | ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms | 2021 | VLDB | 5.5302333e-05 |
| 11,675 | Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering* | 2021 | SIGMOD | 5.093636e-05 |
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