Neural Network applications using Beowulf

Thomas Zheng tzheng at
Tue Nov 19 15:05:15 PST 2002

Hi Eray,

What you said was pretty much true until recently.  In WCCI2002 
( this May, Dr. Hecht-Nielsen from Univeristy of 
California, San Diego, announced his new thalamocortical information 
processing theory, which, I think, is paving the way for next generation AI 
research.  In his special lecture, he showed a couple slides of 
parallel-computing machines he used in his lab.  Even though he never got 
into the details of these machines, from what i know about associative 
memory networks, which are the building blocks of his new theories, it does 
demonstrate highly parallel-implementable features.  And we are talking 
about thousands of nodes  as minimum requirements for these networks to be 

In my opinions, there are tremendous potentials for parallel computing in 
the neural network arena.  The question is what kind of practical/useful 
applications would come out of it.


Thomas Zheng

At 09:40 AM 11/14/2002 +0200, you wrote:
>On Tuesday 12 November 2002 06:24, Robert G. Brown wrote:
> > I actually think that there is room to do a whole lot of interesting
> > research on this in the realm of Real Computer Science.
> >
> > Too bad I'm a physicist...;-)
>Note that most artificial neural network applications don't fall in the realm
>of supercomputing since they would be best suited to hardware
>implementations, or more commonly, serial software.

>We had discussed this with colleagues back at bilkent cs department and we
>could not find great research opportunities in this area. It is a little
>similar to stuff like parallel DFA/NFA systems. You first need an application
>to prove that there is need for problems of that magnitude (more than what a
>serial computer could solve!). What good is a supercomputer for an artificial
>neural network that is comprised of just 20 nodes?
>If of course somebody showed an application that did demand the power of a
>supercomputer it would be very different, then we would get all of our
>combinatorial tools to partition the computational space and parallelize
>whatever algorithm there is :)
>Neural networks being Turing-complete, I assume such a network would bear an
>arrangement radically different from the "multi-layer feed-forward" networks
>that EE people seem to be obsessed with. I have lost my interest in that area
>since they don't seem to demand parallel systems and they are not
>biologically plausible.
>Eray Ozkural (exa) <erayo at>
>Comp. Sci. Dept., Bilkent University, Ankara
>www:  Malfunction:
>GPG public key fingerprint: 360C 852F 88B0 A745 F31B  EA0F 7C07 AE16 874D 539C

Thomas Zheng

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