de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Exploring weak scalability for FEM calculations on a GPU-enhanced cluster

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45566

Strzodka,  Robert
Computer Graphics, MPI for Informatics, Max Planck Society;
Graphics - Optics - Vision, MPI for Informatics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Göddeke, D., Strzodka, R., Mohd-Yusof, J., McCormick, P., Buijssen, S. H., Grajewski, M., et al. (2007). Exploring weak scalability for FEM calculations on a GPU-enhanced cluster. Parallel Computing, 33(10-11), 685-699. doi:10.1016/j.parco.2007.09.002.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-1F27-1
Zusammenfassung
The first part of this paper surveys co-processor approaches for commodity based clusters in general, not only with respect to raw performance, but also in view of their system integration and power consumption. We then extend previous work on a small GPU cluster by exploring the heterogeneous hardware approach for a large-scale system with up to 160 nodes. Starting with a conventional commodity based cluster we leverage the high bandwidth of graphics processing units (GPUs) to increase the overall system bandwidth that is the decisive performance factor in this scenario. Thus, even the addition of low-end, out of date GPUs leads to improvements in both performance- and power-related metrics.