• DocumentCode
    1920670
  • Title

    Cosmology on the Blue Waters Early Science System

  • Author

    O´Shea, B. ; Norman, Michael ; Smith, Brian ; Turk, M. ; Kuhlen, M. ; Wise, John ; Reynolds, Daryl ; Harkness, R. ; Gajbe, M. ; Semeraro, Dave

  • fYear
    2012
  • fDate
    10-16 Nov. 2012
  • Firstpage
    1578
  • Lastpage
    1578
  • Abstract
    The submitted visualization represents work performed by the Enzo PRAC team lead by Brian O\´Shea on the Blue Waters Early Science system. A relatively small test calculation was performed followed by several much larger AMR cosmological runs. The overall scientific goal was to understand how galaxies in the early Universe (the first billion years or so after the Big Bang) grow and evolve, in several statistically-dissimilar environments. Specifically, we looked at a region that is statistically over dense (substantially more galaxies than the average per volume), under dense (the opposite), of average mean density, and, finally, a region that will make a Milky Way-like galaxy at the present day. For each calculation, we used two separate formulations for our sub grid models of star formation and feedback. The simulation visualized in these movies represents the "average" calculations, which are the most statistically comparable to galaxies that have been observed with the Hubble Space Telescope and large ground-based telescopes. The visualization were done using the VisIt volume renderer. The analysis was completely performed on the Blue Waters Early science system. Volume renderings of density and temperature are presented. Each of these simulations was substantially larger than any previous Enzo AMR calculation ever run (as well as larger than any other AMR cosmological simulation ever done). By the end of the run, the calculations have several billion unique resolution elements on six levels of adaptive mesh.
  • Keywords
    astronomy computing; cosmology; galaxies; star formation; AMR cosmological simulations; Blue Waters Early Science System; Enzo PRAC team; Hubble Space Telescope; Milky Way like galaxy; VisIt volume renderer; adaptive mesh; cosmology; early Universe galaxies; galactic evolution; galactic growth; star formation; statistically dissimilar environments; subgrid models; AMR; Cosmology; Enzo; Rendering; VisIt; Volume;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
  • Conference_Location
    Salt Lake City, UT
  • Print_ISBN
    978-1-4673-6218-4
  • Type

    conf

  • DOI
    10.1109/SC.Companion.2012.370
  • Filename
    6496115