Parallel Batch-Dynamic Coreness Decomposition with Worst-Case Guarantees
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3694906.3743328.pdf
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679.84 KB
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Adobe PDF
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1212ca463127ce441f8b9fdfa2cefeb3
Author(s)
Ghaffari, Mohsen
Koo, Jaehyun
Date Issued
July 16, 2025
Publisher
ACM|37th ACM Symposium on Parallelism in Algorithms and Architectures
Citation
Mohsen Ghaffari and Jaehyun Koo. 2025. Parallel Batch-Dynamic Coreness Decomposition with Worst-Case Guarantees. In Proceedings of the 37th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '25). Association for Computing Machinery, New York, NY, USA, 225–239.
Version
Final published version
Abstract
We present the first parallel batch-dynamic algorithm for approximating coreness decomposition with worst-case update times. Given any batch of edge insertions and deletions, our algorithm processes all these updates in poly(log n) depth, using a worst-case work bound of b. poly(log n) where b denotes the batch size. This means the batch gets processed in Õ(b/p) time, given p processors, which is optimal up to logarithmic factors. Previously, an algorithm with similar guarantees was known by the celebrated work of Liu, Shi, Yu, Dhulipala, and Shun [SPAA'22], but with the caveat of the work bound, and thus the runtime, being only amortized.
Description
SPAA ’25, Portland, OR, USA
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-NoDerivatives
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DOI of Published Version
https://doi.org/10.1145/3694906.3743328
