4 ms·
"Even on a 30 nm process, it would be possible to place 25 million cells in a square centimeter, with 10,000 synapses on each cell. And all that would dissipate
by andyl 11y ago
"Even on a 30 nm process, it would be possible to place 25 million cells in a square centimeter, with 10,000 synapses on each cell. And all that would dissipate about a Watt."
Wow - seems like a lot.
Human brain by comparison (sourced by google):
- 12 watts
- 100 billion neurons
- 1000 trillion connections
Computing with memsisters is going to be very interesting.
- deleted 11y ago[deleted]
- alphydan 11y agoput that on a 20cm x 30cm surface (laptop) ... and you have 25m x 600 = 15bn cells, 150 trillion synapses using 600W. If they can ever fabricate such a thing ... those neural networks are going to compute some scary stuff!
- venomsnake 11y ago> If they can ever fabricate such a thing ... those neural networks are going to compute some scary stuff! Do we have to pay extra for Austrian accent?
- thangalin 11y agoThe human brain has between 100 and 500 trillion synapses and consumes a lowly 12 watts. (In contrast, a 12.6 megawatt supercomputer, in 2013, took 40 minutes to simulate one second of biological brain activity.) The article cites 250 billion synapses per watt. For the same 12 watts as a human brain eats up, a set of memristors could simulate three trillion synapses. A cat, in comparison, has 10 trillion. To get 100 trillion synapses, multiply those 12 watts by 33.3 to get 400 watts (the draw of nearly seven 60-watt incandescent bulbs). Since one watt bags us 250 billion synapses and 400 watts is equivalent to a memristor-based human brain, then 400 cm^2 is the area needed to emulate the meekest of human minds. That's nearly the same area as half of a medium Domino's pizza. Certainly is... food for thought.
- neolefty 11y agoDoes that take into account computation speed per synapse/memristor?
- mda 11y agoBrain synapse response time is very slow. Depending on type it is in order of milliseconds.
- vanderZwan 11y agoI guess that's part of why such a large part of our thinking is subconscious parallel processing: as a workaround for this technical limitation.
- sz4kerto 11y ago"In contrast, a 12.6 megawatt supercomputer, in 2013, took 40 minutes to simulate one second of biological brain activity." Just as a note: we are not sure whether that large computer really simulated brain activity or not. The tricky thing in brain research is that we have practically zero* idea about what matters and what can be omitted from the simulation. (For example, the glia cells seem to be important -- until recently, we have disregarded their role.) So at this point even we had an infinitely big computer we could not simulate the brain properly because we don't know what exactly to simulate. *zero means that there's much more we don't know than what we know.
- samatman 11y agoAs I never tire of quipping, if you can't get it high on neurotransmitters, it isn't a neural network.
- dkersten 11y ago"In contrast, a 12.6 megawatt supercomputer, in 2013, took 40 minutes to simulate one second of biological brain activity." Not really a fair comparison. That's like simulating one processor with another and complaining that 1 second of activity took 40 minutes to simulate. If we can implement the NN directly, rather than simulate it, we should expect a much smaller performance gap. If your calculations are correct, that doesn't sound so bad. If we could implement a brain-sized (by number of neurons) neural network in the area as half of a medium Domino's pizza, that seems like a damn good achievement to me!