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Scalable Shared-Memory Hypergraph Partitioning

Gottesbüren, Lars; Heuer, Tobias ORCID iD icon; Sanders, Peter ORCID iD icon; Schlag, Sebastian

Abstract:

Hypergraph partitioning is an important preprocessing step for optimizing data placement and minimizing communication volumes in high-performance computing applications. To cope with ever growing problem sizes, it has become increasingly important to develop fast parallel partitioning algorithms whose solution quality is competitive with existing sequential algorithms.

To this end, we present Mt-KaHyPar, the first shared-memory multilevel hypergraph partitioner with parallel implementations of many techniques used by the sequential, high-quality partitioning systems: a parallel coarsening algorithm that uses parallel community detection as guidance, initial partitioning via parallel recursive bipartitioning with work-stealing, a scalable label propagation refinement algorithm, and the first fully-parallel direct k-way formulation of the classical FM algorithm.

Experiments performed on a large benchmark set of instances from various application domains demonstrate the scalability and effectiveness of our approach. With 64 cores, we observe self-relative speedups of up to 51 and a harmonic mean speedup of 23.5. In terms of solution quality, we outperform the distributed hypergraph partitioner Zoltan on 95% of the instances while also being a factor of 2.1 faster. ... mehr


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Originalveröffentlichung
DOI: 10.1137/1.9781611976472.2
Zugehörige Institution(en) am KIT Institut für Theoretische Informatik (ITI)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 01.2021
Sprache Englisch
Identifikator ISBN: 978-1-61197-647-2
KITopen-ID: 1000132477
HGF-Programm 46.21.02 (POF IV, LK 01) Cross-Domain ATMLs and Research Groups
Erschienen in ALENEX 2021 : SIAM Symposium on Algorithm Engineering and Experiments. Ed.: M. Farach-Colton
Veranstaltung SIAM Symposium on Algorithm Engineering and Experiments (ALENEX 2021), Online, 10.01.2021 – 11.01.2021
Verlag Society for Industrial and Applied Mathematics (SIAM)
Seiten 16–30
Vorab online veröffentlicht am 07.01.2021
Nachgewiesen in arXiv
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