[Beowulf] Re: Beowulf Digest, Vol 15, Issue 16

[Michael Will]

Jim Lux wrote:

>> So you have a calculation problem that's embarrassingly parallel
>> but an infinite parameter space to search.  Seems to me that if
>> this process is to be automated you will need to define a goal
>> function, presumably based primarily on the far field results,
>> and then use some search strategy or other to try to find at
>> least a local "best" design in your parameter space. For instance,
>> this probem might be amenable to a genetic algorithm approach.
>
>
>
> Actually, the ideal "goal evaluator" is me, looking at the results of 
> several runs and comparing them, then telling the "box" which way to 
> go next. As you say, if you could define a goal function with 
> sufficient clarity, then any manner of optimizers could grind away on 
> the problem overnight.  Unfortunately, most real design problems have 
> requirements that are a bit fuzzy:  Don't make it "too big" or "too 
> flimsy".  terms like "flimsy" are hard to encapsulate succinctly in a 
> mathematical formulation (although, gosh, we certainly try, by 
> requiring certain mechanical resonance properties and failure 
> strengths). Much like other things, you know them when you see them.

Which is excactly when you start to engage the well studied 
'fuzzy-logic' control.
There are some people combining those with neuronal networks, but I 
don't see
why it should not be used for any adaptive search. I don't know what the 
state
of the art is with mapping that on a cluster though...
digging through comp.ai.fuzzy could be a starting point, but I only saw one
question without answer to the topic there from albertau at h02.vol.net, maybe
contact him about it if his email address is still valid 10 years after ;-)

Michael

>> I know essentially nothing about antenna design so take the following
>> suggestion with the requisite large crystal of salt.  Can you
>> subdivide the available (flat?) radiating area into a grid of
>> identical squares which are classified as antenna/non-antenna?
>> At that point your parameters may reduce to:  1) number of squares,
>> 2) their distribution.  The first is a single integer and the second
>> is a bit vector (ie, MxN bits, 1 for cells that are
>> antenna, 0 for cells that are not.) This is a simple enough
>> parameter space that a genetic algorithm should be relatively
>> simple to implement.  Hopefully you can make this work with so
>> many itty bitty squares that the little squares are much smaller
>> than the shortest wavelength so that the jaggedy edges won't
>> change the results significantly.
>
>
> Aha... your idea has been anticipated!  Several people have done just 
> this (using a Beowulf, even, for the optimizing).  Randy Haupt did a 
> fair amount of it with wire antennas (and others, I'm sure).  There 
> was also someone at UCLA who designed wireless antennas using just 
> what you describe (adding and removing small patches of conductive 
> surface).  They then fabricated the antennas and tested them.
>
>
>
>> You can employ your design expertise by starting the genetic
>> algorithm with a few designs that you have reason to think might
>> work reasonably well.  Also a bunch of random ones.  Then let
>> the software mutate and recombine to see if it can do any
>> better.
>>
>> Regards,
>>
>> David Mathog
>> mathog at caltech.edu
>> Manager, Sequence Analysis Facility, Biology Division, Caltech
>
>
> James Lux, P.E.
> Spacecraft Radio Frequency Subsystems Group
> Flight Communications Systems Section
> Jet Propulsion Laboratory, Mail Stop 161-213
> 4800 Oak Grove Drive
> Pasadena CA 91109
> tel: (818)354-2075
> fax: (818)393-6875
>
>
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-- 
Michael Will
Penguin Computing Corp.
Sales Engineer
415-954-2887
415-954-2899 fx
mwill at penguincomputing.com 
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