[Crib-list] SPEAKERS: DAVID J. KNEZEVIC and PHUONG HUYNH (MIT) -- Computational Research in Boston Seminar -- Friday, May 7, 2010 -- 12:30 PM -- Room 32-124 (Stata)

[Shirley Entzminger]

			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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