A Parallel Hill-Climbing Refinement Algorithm for Graph Partitioning
2015-11-25
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
A Parallel Hill-Climbing Refinement Algorithm for Graph Partitioning
Authors
Published Date
2015-11-25
Publisher
Type
Report
Abstract
Graph partitioning is an important step in distributing workloads on parallel compute systems,
sparse matrix re-ordering, and VLSI circuit design. Producing high quality graph partitionings
while effectively utilizing available CPU power is becoming increasingly challenging due
to the rising number of cores per processor. This not only increases the amount of parallelism
required of the partitioner, but also the degree partitionings it is to generate. In this work we
present a new shared-memory parallel k-way method of refining an existing partitioning that
can break out of local minima. Our method matches the quality of the current high-quality
serial refinement methods, and achieves speedups of 5.7-16.7x using 24 threads, while exhibiting
only 0.52% higher edgecuts than when run serially. This is 6.3x faster than other parallel
refinement methods.
Keywords
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
LaSalle, Dominique; Karypis, George. (2015). A Parallel Hill-Climbing Refinement Algorithm for Graph Partitioning. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215984.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.