60th Annual Meeting of the Divison of Fluid Dynamics
Volume 52, Number 12
Sunday–Tuesday, November 18–20, 2007;
Salt Lake City, Utah
Session BS: Mini-Symposium I: Turbulence Simulations and Advanced Cyberinfrastructure
10:34 AM–12:44 PM,
Sunday, November 18, 2007
Salt Palace Convention Center
Room: Ballroom EG
Chair: P.K. Yeung, Georgia Institute of Technology
Abstract ID: BAPS.2007.DFD.BS.4
Abstract: BS.00004 : Analysis of Turbulence Datasets using a Database Cluster: Requirements, Design, and Sample Applications*
11:52 AM–12:18 PM
Preview Abstract
Abstract
Author:
Charles Meneveau
(Johns Hopkins University)
The massive datasets now generated by Direct Numerical
Simulations (DNS) of turbulent flows create serious new
challenges. During a simulation, DNS provides only a few time
steps at any instant, owing to storage limitations within the
computational cluster. Therefore, traditional numerical
experiments done during the simulation examine each time slice
only a few times before discarding it. Conversely, if a few large
datasets from high-resolution simulations are stored, they are
practically inaccessible to most in the turbulence research
community, who lack the cyber resources to handle the massive
amounts of data. Even those who can compute at that scale must
run simulations again forward in time in order to answer new
questions about the dynamics, duplicating computational effort.
The result is that most turbulence datasets are vastly
underutilized and not available as they should be for creative
experimentation. In this presentation, we discuss the desired
features and requirements of a turbulence database that will
enable its widest access to the research community. The guiding
principle of large databases is ``move the program to the data''
(Szalay et al. ``Designing and mining multi-terabyte Astronomy
archives: the Sloan Digital Sky Survey,'' in ACM SIGMOD, 2000).
However, in the case of turbulence research, the questions and
analysis techniques are highly specific to the client and vary
widely from one client to another. This poses particularly hard
challenges in the design of database analysis tools. We propose a
minimal set of such tools that are of general utility across
various applications. And, we describe a new approach based on a
Web services interface that allows a client to access the data in
a user-friendly fashion while allowing maximum flexibility to
execute desired analysis tasks. Sample applications will be
discussed. This work is performed by the interdisciplinary ITR
group, consisting of the author and Yi Li(1), Eric Perlman(2),
Minping Wan(1), Yunke Yang(1), Randal Burns(2), Shiyi Chen(1),
Gregory Eyink (3) Alex Szalay (4) with the following departmental
affiliations: (1) Mechanical Engineering, (2) Computer Science
(3) Applied Mathematics \& Statistics, (4) Physics and Astronomy.
*This research is funded by a National Science Foundation ITR/ASE grant.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2007.DFD.BS.4