Brain-inspired circuit board 9000 times faster than an average PC

Bioengineers at Stanford University have developed microchips based on the human brain that are more energy efficient and up to 9000 times faster than the typical PC.

Bioengineers at Stanford University have developed microchips based on the human brain that are more energy efficient and up to 9000 times faster than the typical PC.

(Credit: Stanford University)

Simulating the human brain is one of the holy grails of computing — but it's extraordinarily difficult to do. Just last year, the longest simulation of brain activity to date was achieved. It used the fourth-most powerful computer in the world, Japan's K Computer, 705,024 processor cores, and running at speeds of over 10 petaflops. The simulation, using 92,944 processors, took 40 minutes to simulate one second of brain activity over the equivalent of one per cent of the brain, around 10.4 trillion synapses.

As for why it's important — if we could get a computer to operate with the power and speed of the human brain, we could make some incredibly advanced robots, or prosthetic limbs that operate with the speed and complexity of our own movements. It could also help us understand better how the brain actually works — a largely mysterious subject.

A team of bioengineers at Stanford University has created a circuit board that is able to simulate the activity of one million neurons — around seven billion synaptic connections — in real-time. At about the size of an iPad, the board — called the Neurogrid — consists of 16 custom-designed "Neurocore" chips made using 15-year-old technology laid out in a tree network. This is because it uses analogue computation alongside digital.

"Analog computation constrains the number of distinct ion-channel populations that can be simulated—unlike digital computation, which simply takes longer to run bigger simulations," the Neurogrid website explains. "Digital communication constrains the number of synaptic connections that can be activated per second, unlike analog communication, which simply sums additional inputs onto the same wire. Working within these constraints, Neurogrid achieves its goal of simulating multiple cortical areas in real-time by making judicious choices."

Using analogue computation also keeps power requirements low — 100,000 times less power than a supercomputer, according to principal investigator Kwabena Boahen, who has been working on the Neurogrid since 2006. A supercomputer requires one million Watts of power to simulate one million neurons, while the human brain uses just 20 Watts for 100 billion neurons. But the Neurogrid isn't quite as energy-efficient as the brain. "The human brain, with 80,000 times more neurons than Neurogrid, consumes only three times as much power," Boahen wrote in an article for the most recent issue of Proceedings of the IEEE.

Boahen and his team would like to see the Neurogrid developed for applications such as prosthetics — but first, the cost of creating the Neurogrid will need to be lowered. At the moment, a Neurogrid costs about US$40,000, but switching to modern manufacturing methods could reduce the price to as low as US$400, the team believes.

You can read more about the Neurogrid on the Stanford University website.

 

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