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[Submitted on 26 May 2022 (v1), last revised 30 Jun 2022 (this version, v3)]

Title:More Recent Advances in (Hyper)Graph Partitioning

Authors:Ümit V. Çatalyürek, Karen D. Devine, Marcelo Fonseca Faraj, Lars Gottesbüren, Tobias Heuer, Henning Meyerhenke, Peter Sanders, Sebastian Schlag, Christian Schulz, Daniel Seemaier, Dorothea Wagner
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Abstract: In recent years, significant advances have been made in the design and evaluation of balanced (hyper)graph partitioning algorithms. We survey trends of the last decade in practical algorithms for balanced (hyper)graph partitioning together with future research directions. Our work serves as an update to a previous survey on the topic. In particular, the survey extends the previous survey by also covering hypergraph partitioning and streaming algorithms, and has an additional focus on parallel algorithms.
Subjects: Data Structures and Algorithms (cs.DS); Machine Learning (cs.LG)
Cite as: arXiv:2205.13202 [cs.DS]
  (or arXiv:2205.13202v3 [cs.DS] for this version)
  https://doi.org/10.48550/arXiv.2205.13202
arXiv-issued DOI via DataCite

Submission history

From: Christian Schulz [view email]
[v1] Thu, 26 May 2022 07:38:17 UTC (1,090 KB)
[v2] Sat, 28 May 2022 09:24:56 UTC (1,090 KB)
[v3] Thu, 30 Jun 2022 15:40:40 UTC (1,051 KB)
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