[Crib-list] SPEAKERS: Lothar Wenzel and Darren Schmidt (National Instruments) -- Computational Research in Boston Seminar -- Friday, 06/01/2007 -- TIME: 12:30 PM -- LOCATION: Room 32-141 (Stata Center) (fwd)

[Shirley Entzminger]

T O D A Y . . .


 			COMPUTATIONAL RESEARCH in BOSTON SEMINAR

Date:		FRIDAY, JUNE 1, 2007
Time:		12:30 PM
Location:	Building 32, Room 141 (Stata Center)

Pizza and beverages will be provided at 12:15 PM outside Room 32-141.


Title:		ATTACKING PROCESSOR ARCHITECTURES FROM TWO
 		MATHEMATICAL ANGLES


Speakers:	LOTHAR WENZEL and DARREN SCHMIDT
 		National Instruments


ABSTRACT:

In the past decade, the evolution of processor architectures has placed 
exceptional demands on the deployment of mathematical algorithms. Portable 
devices contain new more powerful embedded processors making it possible to 
solve more advanced mathematical problems.  The increased use of DSPs and 
FPGAs requires both specialized libraries and tools for developing algorithms 
for these targets.  Now, with the move to multi-core processors in mainstream 
PCs, the numeric libraries optimized for single core processors struggle to 
make use of the additional processing resources.  In the worst cases, the 
performance of these libraries degrades on multi-core systems due to data 
dependencies and communication overhead.

Recognizing these challenges, National Instruments (NI) is working on two 
fronts to make the development and deployment of numeric algorithms easier for 
the math and engineering communities.  First, NI has joined with vendors in 
the mathematics industry (INRIA, MapleSoft, and PTC) and scientist/engineers 
in academia, to form the Numerical Mathematics Consortium (NMC).  The NMC is 
defining the fundamental mathematical components of math algorithms used in a 
wide range of applications.  This initiative follows the successes of prior 
de-facto standards, such as BLAS and LAPACK, and defines the next generation 
of mathematical functions found in almost all general-purpose math packages.

The NMC's approach to the standard is significantly different from recent 
standards efforts.  By specifying function semantics and not syntax, the NMC's 
function definitions are applicable to many mathematical arenas. They provide 
a solid foundation for math algorithm development and allow vendors to promote 
their programming paradigm which may target specialized hardware.  This 
approach reduces the learning curve for both academia and industry by 
supplying a uniform, consistent set of math definitions for fundamental 
functions.  For those wishing to develop optimal code solutions for a specific 
processor, the NMC defines the basic set of math functions needed to support 
algorithm development on any platform.

While NI works with those in the NMC to bridge the gap between present-day 
algorithm development and tomorrow's architecture, we are also committed to 
solving present-day engineering problems for real world, real-time 
applications.  The availability of low-cost multi-core systems enables 
LabVIEW, NI's graphical system design tool, to combine sophisticated data 
acquisition systems with demanding numerical tasks.  In a typical scenario, 
information about a system is based on direct or derived measurements and the 
acquired data is used to solve linear or even nonlinear elliptic partial 
differential equations.  The results generated by the PDE-solver might be used 
as feedback to the running process.  Such a system can be very demanding from 
a real-time standpoint and might require loop-times in the 1 ms range.

To comply with such specifications, multi-core architectures and other 
techniques such as FPGA-based components and high-speed networking are 
supported by LabVIEW.  We provide benchmarks for specific elliptic PDE solvers 
based on 8- and 16-core machines using standard quad-core processors where 
multi-board deployments require fast networking.  We also report multi-core 
performance numbers for more elementary operations such as FFT, DST and matrix 
operations.

You can find more information on the NMC at http://www.numath.org and on NI's 
LabVIEW product line at http://www.ni.com/labview.

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Massachusetts Institute of Technology
Cambridge, MA  02139

http://www-math.mit.edu/crib

For information on CRiB, contact:

Alan Edelman:  edelman at math.mit.edu
Steven G. Johnson:  stevenj at math.mit.edu
Jeremy Kepner:  kepner at ll.mit.edu