Parallel Batch-Dynamic Coreness Decomposition with Worst-Case Guarantees

Fuente: arXiv
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Main Authors: Ghaffari, Mohsen, Koo, Jaehyun
Format: Preprint
Published: 2025
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author Ghaffari, Mohsen
Koo, Jaehyun
author_facet Ghaffari, Mohsen
Koo, Jaehyun
contents 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 $ \text{poly}(\log n)$ depth, using a worst-case work bound of $b\cdot \text{poly}(\log n)$ where $b$ denotes the batch size. This means the batch gets processed in $\tilde{O}(b/p)$ 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_06334
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Parallel Batch-Dynamic Coreness Decomposition with Worst-Case Guarantees
Ghaffari, Mohsen
Koo, Jaehyun
Data Structures and Algorithms
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 $ \text{poly}(\log n)$ depth, using a worst-case work bound of $b\cdot \text{poly}(\log n)$ where $b$ denotes the batch size. This means the batch gets processed in $\tilde{O}(b/p)$ 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.
title Parallel Batch-Dynamic Coreness Decomposition with Worst-Case Guarantees
topic Data Structures and Algorithms
url https://arxiv.org/abs/2507.06334