Work

Parallel Batch-Dynamic Maximal Matching with Constant Work per Update

Year: 2025

Type: conference-paper

Abstract: We present a work optimal algorithm for parallel fully batch-dynamic maximal matching against an oblivious adversary. It processes batches of updates (either insertions or deletions of edges) in constant expected amortized work per edge update, and in O (log3 m) depth per batch whp, where m is the maximum number of edges in the graph over time. This greatly improves on the recent result by Ghaffari and Trygub (2024) that requires O (log9 m) amortized work per update and O (log4 m) depth per batch, both whp.

Source: ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)

DOI: 10.1145/3694906.3743313

Authors: Guy E. Blelloch, Andrew C. Brady

Institution: Carnegie Mellon University

Language: English

Topic: Complexity and Algorithms in Graphs

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, Universitas Brawijaya

Awards: G3590458404, Collaborative Research: PPoSS: LARGE: Unifying Software and Hardware to Achieve Performant and Scalable Frictionless Parallelism in the Heterogeneous Future, SPX: Parallel Models and Algorithms for Emerging Memory Systems