[Crib-list] TODAY: SPEAKERS: DAVID J. KNEZEVIC and PHUONG HUYNH (MIT) -- Computational Research in Boston Seminar -- Friday, May 7, 2010 -- 12:30 PM -- Room 32-124 (Stata) (fwd)
Shirley Entzminger
daisymae at math.mit.edu
Fri May 7 09:37:18 EDT 2010
T O D A Y . . .
COMPUTATIONAL RESEARCH in BOSTON SEMINAR
DATE: FRIDAY, May 7, 2010
TIME: 12:30 PM
LOCATION: Building 32, Room 124 (Stata Center)
Pizza and beverages will be provided at 12:15 PM outside Room 32-124.
TITLE: Supercomputing on a Smartphone via Model Order
Reduction with Rigorous Error Bounds
SPEAKER: DAVID J. KNEZEVIC and PHUONG HUYNH
(Massachusetts Institute of Technology)
ABSTRACT:
Numerical methods for partial differential equations (PDEs) are a crucial
tool in modern science and engineering, but these methods are often highly
demanding in terms of computational resources. In many engineering
contexts the ability to rapidly and accurately solve PDEs on a portable
device (i.e. "in the field") would be extremely valuable, but this is
clearly out of reach of classical numerical methods. However, by
employing model reduction --- more specifically, the Certified Reduced
Basis method --- we are able to make high-fidelity scientific computing
available on deployed platforms with limited processor speed and memory.
The Certified Reduced Basis method applies to a class of PDEs of
significant engineering interest; it involves a computationally expensive
Offline stage in which we generate a reduced model followed by the
invocation of a very cheap Online stage in which the reduced model is
evaluated in real-time for user-specified parameters. We discuss the
realization of this framework via a two-level hierarchy of computational
architectures: we employ a TeraGrid supercomputer for the Offline and a
Nexus One Android smartphone for the Online. The crucial component of our
approach that yields "supercomputing on a smartphone" in a rigorous sense
is that we compute a posteriori error bounds for the reduced order model
with respect to the high-fidelity solution.
In this talk we emphasize the computational aspects of this hierarchical
architecture: parallelization of the Offline stage in space and parameter;
efficient implementation of the Online stage for input-output evaluation
and visualization on `thin platforms.' We illustrate our methodology with
examples and demonstrations from heat transfer, solid mechanics,
acoustics, and fluid dynamics.
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