Replicated hypergraph partitioning
Author
Selvitopi, Reha Oğuz
Advisor
Aykanat, Cevdet
Date
2010Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Hypergraph partitioning is recently used in distributed information retrieval (IR)
and spatial databases to correctly capture the communication and disk access
costs. In the hypergraph models for these areas, the quality of the partitions
obtained using hypergraph partitioning can be crucial for the objective of the
targeted problem. Replication is a widely used terminology to address different
performance issues in distributed IR and database systems. The main motivation
behind replication is to improve the performance of the targeted issue at the cost
of using more space.
In this work, we focus on replicated hypergraph partitioning schemes that improve
the quality of hypergraph partitioning by vertex replication. To this end,
we propose a replicated partitioning scheme where replication and partitioning
are performed in conjunction. Our approach utilizes successful multilevel and
recursive bipartitioning methodologies for hypergraph partitioning. The replication
is achieved in the uncoarsening phase of the multilevel methodology by
extending the efficient Fiduccia-Mattheyses (FM) iterative improvement heuristic.
We call this extended heuristic replicated FM (rFM). The proposed rFM
heuristic supports move, replication and unreplication operations on the vertices
by introducing new algorithms and vertex states. We show rFM has the same
complexity as FM and integrate the proposed replication scheme into the multilevel
hypergraph partitioning tool PaToH. We test the proposed replication
scheme on realistic datasets and obtain promising results.