• DocumentCode
    649469
  • Title

    Damaris/Viz: A nonintrusive, adaptable and user-friendly in situ visualization framework

  • Author

    Dorier, Matthieu ; Sisneros, Robert ; Peterka, Tom ; Antoniu, Gabriel ; Semeraro, Dave

  • Author_Institution
    ENS Cachan Brittany, IRISA Rennes, Rennes, France
  • fYear
    2013
  • fDate
    13-14 Oct. 2013
  • Firstpage
    67
  • Lastpage
    75
  • Abstract
    Reducing the amount of data stored by simulations will be of utmost importance for the next generation of large-scale computing. Accordingly, there is active research to shift analysis and visualization tasks to run in situ, that is, closer to the simulation via the sharing of some resources. This is beneficial as it can avoid the necessity of storing large amounts of data for post-processing. In this paper, we focus on the specific case of in situ visualization where analysis codes are collocated with the simulation´s code and run on the same resources. It is important for an in situ technique to require minimum modifications to existing codes, be adaptable, and have a low impact on both run times and resource usage. We accomplish this through the Damaris/Viz framework, which provides in situ visualization support to the Damaris I/O middleware. The use of Damaris as a bridge to existing visualization packages allows us to (1) reduce code moditication to a minimum for existing simulations, (2) gather capabilities of several visualization tools to offer a unified data management interface, (3) use dedicated cores to hide the run time impact of in situ visualization and (4) efficiently use memory through a shared-memory-based communication model. Experiments are conducted on Blue Waters and Grid´5000 to visualize the CM1 atmospheric simulation and the Nek5000 CFD solver.
  • Keywords
    data analysis; data visualisation; middleware; resource allocation; Blue Waters; CM1 atmospheric simulation; Damaris input-output middleware; Grid5000; Nek5000 CFD solver; analysis tasks; computational fluid dynamics; in situ visualization framework; large-scale computing; resource sharing; shared-memory-based communication model; visualization packages; visualization tasks; Dedicated Cores; Exascale Computing; I/O; In Situ Visualization; Multicore Architectures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Large-Scale Data Analysis and Visualization (LDAV), 2013 IEEE Symposium on
  • Conference_Location
    Atlanta, GA
  • Type

    conf

  • DOI
    10.1109/LDAV.2013.6675160
  • Filename
    6675160