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From: andrew@dtg.nsc.com (Lord Snooty @ The Giant Poisoned Electric Head       )
Newsgroups: comp.ai,comp.ai.neural-nets
Subject: Re: Parallelism, Real vs. Simulated: A Query
Summary: other factors
Message-ID: <172@berlioz.nsc.com>
Date: 10 Oct 89 00:08:51 GMT
References: <17820@bellcore.bellcore.com> <12449@boulder.Colorado.EDU>
Organization: National Semiconductor, Santa Clara
Lines: 28

In article <12449@boulder.Colorado.EDU>, bill@boulder.Colorado.EDU writes:
> >I have a simple question: What capabilities of PDP systems do and
> >do not depend on the net's actually being implemented in parallel,
> >rather than just being serially simulated? Is it only speed and
> >capacity parameters, or something more?
> >Stevan Harnad     (harnad@confidence.princeton.edu)

> Since the PDP device is a physical object, it is governed by a set
> of differential equations, and those equations can be solved to any
> desired accuracy by a serial device.  (It may take a long time to solve
> them, though.)  If the PDP system is chaotic (in the mathematical sense),
> then no simulation will ever be able to _duplicate_ its behavior, but
> the simulation will still be able to imitate it in the sense of being
> equally unpredictable by the user. 

I'd like to add a caveat to this view: the issue of exact implementation
is being glossed over. In a "real" BP NN, weight updates and weighted
activation arrival times may be purely asynchronous. The "batch update"
versus "per input" update paradigms also give room for difference.
Although both methods are in principle simulatable in a serial fashion,
I'm not quarrelling with bill's response. However, if the asynchronous
case is driven differently by the simulator's random number generator
w.r.t. the  "real" NN, and local minima and/or instability problems exist,
the performances will not match up.
-- 
...........................................................................
Andrew Palfreyman		and the 'q' is silent,
andrew@dtg.nsc.com		as in banana			 time sucks