Balanced brainchip design

From: Dani Eder (
Date: Fri Apr 13 2001 - 13:29:14 MDT

I've been giving some thought to what a balanced
design for a future 'brainchip' would be. By about
2014, the Semiconductor Industry Association projects
technology would allow a single chip with about 8
Gbytes of memory and 8 simple CPU cores that put out
about 8 GFlop each. Such a chip should cost about
$12 (the same as a high end memory chip today), and
a complete system built with these chips could cost
around $30 per chip.

I previously determined that an engineer-replacing
system would be worth around $3M, so we can afford
to incorporate about 100K of these chips in a system.
If we are running a simulated human cortex type AI,
allow 3 bytes of description per synapse. Then each
neuron would require about 32K, and therefore each
chip would model 0.25 million neurons. The whole
system would model 25 billion neurons, or roughly
a human cortex's worth.

Simulating 2.5 billion synapses at 100 Hz with 1 byte
of calculation per synapse requires 64 GFlops, which
is what our 8 processor cores can provide.

To get an idea of off-chip I/O requirements, assume
that neurons are arranged in a block of 63 x 63 x 63
units (63 being the cube root of 250,000). And
assume that all 10,000 synapses of the surface neurons
are connected to neurons outside the block. This
requires off chip I/O in the model. The minimal
data carried off chip is "I'm firing now", which
requires 1 bit per synapse. Therefore 24 Gbits of
data need to move off chip, and presumably the same
coming in.

The SIA projects being able to support up to 1500
data lines per chip package, so each data line would
be running at 32 Mhz, which is well within current
technology. Even if every synapse of every neuron
leads off chip, the data lines would need to run at
333 Mhz, which is only slightly above current data
bus speeds.

It may be required to carry more than 1 bit of data
per synapse firing off chip, or it may be possible
to do some data compression, but at least the numbers
seem to indicate a brain-simulating AI is not
completely out of the question for 2014 technology.


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