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
Link To Document