Investigation of load balancing scalability in space plasma simulations
buir.contributor.author | Aykanat, Cevdet | |
dc.citation.epage | 562 | en_US |
dc.citation.spage | 558 | en_US |
dc.citation.volumeNumber | 7782 | en_US |
dc.contributor.author | Türk, Ata | en_US |
dc.contributor.author | Demirci, Gündüz V. | en_US |
dc.contributor.author | Aykanat, Cevdet | en_US |
dc.contributor.author | Von Alfthan, S. | en_US |
dc.contributor.author | Honkonen I. | en_US |
dc.coverage.spatial | Helsinki, Finland | en_US |
dc.date.accessioned | 2016-02-08T12:08:36Z | |
dc.date.available | 2016-02-08T12:08:36Z | |
dc.date.issued | 2013 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description | Conference name: 11th International Conference, PARA 2012 | en_US |
dc.description | Date of Conference: June 10-13, 2012 | en_US |
dc.description.abstract | In this study we report the load-balancing performance issues that are observed during the petascaling of a space plasma simulation code developed at the Finnish Meteorological Institute (FMI). The code models the communication pattern as a hypergraph, and partitions the computational grid using the parallel hypergraph partitioning scheme (PHG) of the Zoltan partitioning framework. The result of partitioning determines the distribution of grid cells to processors. It is observed that the initial partitioning and data distribution phases take a substantial percentage of the overall computation time. Alternative (graph-partitioning-based) schemes that provide better balance are investigated. Comparisons in terms of effect on running time and load-balancing quality are presented. Test results on Juelich BlueGene/P cluster are reported. © 2013 Springer-Verlag. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T12:08:36Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2013 | en |
dc.identifier.doi | 10.1007/978-3-642-36803-5_46 | en_US |
dc.identifier.doi | 10.1007/978-3-642-36803-5 | en_US |
dc.identifier.issn | 0302-9743 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/28020 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Springer, Berlin, Heidelberg | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1007/978-3-642-36803-5_46 | en_US |
dc.relation.isversionof | https://doi.org/10.1007/978-3-642-36803-5 | en_US |
dc.source.title | Applied Parallel and Scientific Computing | en_US |
dc.subject | Communication pattern | en_US |
dc.subject | Computation time | en_US |
dc.subject | Computational grids | en_US |
dc.subject | Data distribution | en_US |
dc.subject | Finnish | en_US |
dc.subject | Grid cells | en_US |
dc.subject | Hypergraph | en_US |
dc.subject | Hypergraph partitioning | en_US |
dc.subject | Load-Balancing | en_US |
dc.subject | partitioning | en_US |
dc.subject | Partitioning frameworks | en_US |
dc.subject | Performance issues | en_US |
dc.subject | petascaling | en_US |
dc.subject | Running time | en_US |
dc.subject | Space plasmas | en_US |
dc.subject | Plasma simulation | en_US |
dc.subject | Network management | en_US |
dc.title | Investigation of load balancing scalability in space plasma simulations | en_US |
dc.type | Conference Paper | en_US |
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