X-Message-Number: 102
From arpa!A.ISI.EDU!TKD Mon Jun 26 07:42:23 EDT 1989
Date: Mon 26 Jun 89 07:42:23-EDT
From: Thomas Donaldson <>
Subject: Re: CRYONICS mailing list #94 - Brain Computational Memory Limits
In-Reply-To: Message from "" of Sun 25 Jun 89 21:39:57-EDT
Message-ID: <>


This is a commentary on Ralph Merkle's "Computational Power" article.


I read Ralph Merkle's paper with some interest. If I examined his figures
closely I might find reasons to doubt his estimate by as much as a factor of
10, but that is trivia. However his paper does (implicitly) raise a central
issue much more important: what is the SIGNIFICANCE of his computational power
estimate, anyway?  Ralph or anyone can spend much effort making a numerically
and biologically valid estimate of almost any number we care to name.  We can
compute the topological index of the human brain, its area when spread over a
flat surface, its reflectivity to light. Without explicit discussion of the
significance of such measures the effort is incomplete.

For several years now I've been involved directly in the parallel computer
industry. When I originally got my doctorate, Computer Science as a discipline
did not exist, nor did most of the theory of computation and programming
developed since then.  After spending a long time on theoretical mathematics
(even writing one book), I worked for over 3 years with one company, SAXPY,
which fell apart (I believe because of too much salesmanship combined with too
little substance, until too late).  The SAXPY 1-M was what is known as a SIMD
machine.  I'm now working with another company developing software for a MIMD
local memory machine, working much like the hypercube but probably far less
expensive.  It's a very different machine, different problems, different

Even as someone developing algorithms and writing programs in the back room,
I have not failed to notice what goes on in front. In front we have Marketing,
consisting of gentlemen in fine suits.  Marketing must compare "our" computer
with "theirs".  What measure does Marketing seize upon for comparison?
"Computational Power", of course!

What has come most to my mind when I observe this travelling circus is that of
how crude, even stupid, a measure Computational Power actually is. For a long
time, Marketing for the SAXPY 1-M trumpeted its capability of doing 1000
Megaflops far less expensively than Crays. What Marketing never explained was
that it could only achieve that figure on a narrow range of problems. On
others it might, on a good day, equal an old 8088 IBM PC.  Its merits lay in
the specific problems for which it was designed. 

If we deal solely with a von Neumann sequential machine Computational Power
makes a lot of sense.  The machine must proceed on a straight road.  Its
velocity on that road accurately measures its effectiveness.  For parallel
machines, including our brains and the IBM TF-1, there is no straight road
or even any single road. One machine with officially vast CP looks woefully
pathetic on some problems which another machine, with much smaller CP, races
through.  The relation is reversed if we change the problems.  We have every
reason to believe that the same will happen when we try to make some
(arbitrary, officially with godlike CP) machine imitate a human brain.

The issue becomes even deeper than this.  Because most of our machines now are
sequential, we can make a clear distinction between "software" and "hardware".
The hardware is the machine which runs along the route set out by the software.
For parallel machines, particularly those, like hypercubes, consisting of many
processors with local memory communicating with one another, that elementary
Computer Science distinction breaks down.  Choosing the right interconnections
between processors is at least as important as writing software modules which
run on each one. We aim for a combined system achieving our goals.  Imitating
a human brain with such a computer is indeed VERY simple: except for the
design of BOTH HARDWARE AND SOFTWARE, we can consider the problem solved.
How many, then, will go away happy with a figure for Computational Power?

I've personally found involvement with parallelism quite fascinating.  It's
also my personal belief that a LOT of the Computer Science theory developed
for sequential machines simply does not apply to parallel machines.  We need
to work out new ways to structure software; old ideas aren't enough.  We must
develop a lot anew and throw Yourdon out the window.  There's pioneering and
lots of fascination.

As for imitating the human brain, I don't think that SPECIFIC task would even

be wise.  Of course Ralph intends broader and more powerful abilities than that.
If we keep our noses to the grindstone someday we'll look up and see we've
achieved those aims.  Computational Power, though, by then will be a forgotten
concept except among historians of ideas.

Rate This Message: http://www.cryonet.org/cgi-bin/rate.cgi?msg=102