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From: csimmons@oracle.COM (Charles Simmons)
Newsgroups: sci.nanotech
Subject: Re: How big is a brain?
Message-ID: <8903240502.AA22884@athos.rutgers.edu>
Date: 23 Mar 89 10:44:13 GMT
References: <8903230413.AA09069@athos.rutgers.edu>
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In article <8903230413.AA09069@athos.rutgers.edu> shields@yunccn.UUCP (Paul Shields) writes:
>
>In article <8903100502.AA24611@athos.rutgers.edu>, bpendlet@esunix.UUCP
> (Bob Pendleton) writes:
>>After spending a frustrating evening with my Britanica I still haven't
>>found out just how much storage, how many instructions/second, how
>>many simulated nuerons, or what ever, are needed to simulate the
>>function of a human brain.
>
>I've been told that the human brain has from 60 to 90 billion neurons.
>
>>Just what are the design parameters for a machine that would be needed
>>to upload a human mind?
>
>Problem 1: Design a chip to simulate a bunch of neurons.

Ah!  One of my favorite subjects.  One of the people I've talked to
who studys neuro-psychology suggests that the estimated number of
neurons may be as large as 10^14.  That would be about 1000 times
more neurons than you're estimating.

Of possible interest, a neuron has direct connections with around 1000 or
so other neurons, and there may be some reason to believe that it
is the interconnections that make the brain interesting, rather
than the processing capabilities of a neuron.

>An estimate:  if we can simulate a neuron with a few thousand "circuits",
>we can probably simulate close to a hundred with the same circuits, since
>the transistors switch much faster than neurons react.  Assume that with
>100000 circuits (near the chip space of the 80286 processor,) we could
>simulate 1000 neurons in real time on one chip with current technology.
>Then we'd be talking on the order of 60 to 90 million chips (= 2^26) in a
>network, for each brain to be simulated.

In the above paragraph, I think we also need to specify the clock rate
at which the "circuits" are running.  I'd like to see this estimate
be derived in terms of transistors and Mhz.  For example, maybe we
need 400,000 transistors running at a clock rate of 16 Mhz to simulate
1,000 neurons in real time.  Since the number of neurons that can be
simulated will increase if we increase either the number of available
transistors, or if we increase the clock rate, we might want to use
a term like "transistors-Mhz" or "Mthz".  (This is millions of
"transistor-cycles" per second.)

We note that recent labratory chips (the i860) incorporate around
2^20 transistors running at a clock rate of 50 Mhz.  This corresponds
to a little less than 2^26 Mthz on a chip.  We also note that speed and
density of chips each increase by a factor of two around every 18 months.
So, every 3 years we should be able to increase the exponent here by 4.

>You bet.  I ask myself these questions whenever I encounter new technology.
>With chip density doubling every two years or so, I can imagine that a 
>project of this scale might be feasible in about a decade. The standard
>conventional memory unit in the year 2001 could be the 4 giga-bit chip, 
>since memory technologies will be hitting the 32-bit address barrier around
>that time. (Remember the 64K barrier?)  Processor speeds should be approaching
>100 MHz at that time (assuming GaAs technology is delayed due to fabrication
>problems.)

I guess I pretty much agree with your estimate of 4 Gigabit chips in 2001.
I think your estimate of 100 Mhz is way low.  John Mashey at MIPS is
predicting 300 to 400 Mhz clock rates by around 1995.  (MIPS builds
processors, so Mashey's estimate should be mildly reasonable.)  Currently,
we've got 4 Megabit chips just now shipping in small quantities, and 32 Mhz
processors are common.  So, if we have 4 Gigabit chips starting to ship
in 2001, we should have 32 Ghz processors running around.  (Hmmm...
Sanity check...  At 1 Ghz, light can travel 1 foot in one clock cycle.
At 32 Ghz, the "clock-width" is well below an inch...)


If this subject is of widespread and long-term interest, it might
be interesting to develop an equation to describe the number of
transitor-cycles needed to simulate a human brain.  For example,
a while back some astronomers were pondering the number of intelligent
civilizations that exist in the galaxy.  They developed an equation
that contained the number of stars in the galaxy, the fraction of
stars that were class G stars, the average number of planets per star,
the fraction of planets that were neither too close nor too far from
their parent star, and the average lifespan of an intelligent civilization.

For most of the parameters in the equation, the actual value of the
parameter isn't known.  But, various estimates can be plugged in for
each parameter, and as new information is obtained, the actual parameter
values can be refined.

So, as a first attempt to develop such an equation for determining
the number of transitor-cycles needed to simulate the human brain,
let's define the following parameters:

	N -- The number of Neurons in the human brain.

	S -- The fraction of neurons that actually need to be Simulated.
	     For example, maybe 90% of the neurons in the human brain
	     don't do anything, and hence don't need to be simulated.

	T -- The number of Transistor-cycles needed to simulate a
	     single neuron.

	C -- The number of transistor-cycles that can be crammed onto
	     a silicon Chip using some given technology.

	B -- The number of neuron simulating chips that can be
	     crammed into a Box of reasonable size for a reasonable cost
	     using the same technology as that assumed for parameter C.
	     (For reasonable size, let's restrict ourselves to 10,000
	     cubic feet.)

Using the above parameters, it appears that the question we would be
attempting to answer is "in what year will we be able to build a
10,000 cubic foot box (or smaller) that can simulate a human brain?"

We need to simulate S*N neurons.  This requires T*S*N transistor-cycles.
For a given technology, we need (T*S*N)/C chips to simulate a brain,
or we need ( (T*S*N)/C ) / B boxes to simulate a brain.

Hmmm...  Needs work.  Any volunteers?

-- Chuck

P.S.

How hard will it be to actually simulate a neuron in silicon?  ("Very hard"
is not a sufficient answer.)  Do we have to simulate the location and
movement of most molecules in the neuron?  That is, is a significant
fraction of the state information of a neuron stored in the chemical
composition of the neuron?  Or can we get by with a piece of hardware
that looks like an op-amp that has about 500 inputs and 500 outputs?