Energy Efficient Brain Simulator Outperforms Supercomputers

Thursday, April 25, 2013

 Computer Science

The emerging field of neuromorphic engineering seeks to replicate the brain's extraordinary computational abilities using innovative hardware and software applications. At Kwabena Boahen's laboratory at Stanford University, his most recent accomplishment is a new computing platform called Neurogrid, which simulates the activity of 1 million neurons.

According to Kwabena Boahen, Ph.D., IBM's Blue Gene and other supercomputers still do not compare to the computational power of the brain itself.



Graduate students Sam Fok (left) and Alex Neckar (right) hold the brain-inspired computational platform "Neurogrid," which can simulate the activity of 1 million neurons in real time. In June 2012, Fok and Neckar received the $100,000 Qualcomm Innovation Fellowship in recognition of their work with Neurogrid. Image Source: Samir Menon
Boahen works at the forefront of a field called neuromorphic engineering, which seeks to replicate the brain's extraordinary computational abilities using innovative hardware and software applications. His new system called Neurogrid simulates a million neurons connected by billions of synapses in real-time, rivaling Blue Gene's performance while consuming a 100,000 times less energy—five watts instead of a megawatt.

Neurogrid is not a supercomputer. It can't be used to simulate the big bang, or forecast hurricanes, or predict epidemics. But what it can do sets it apart from any computational platform on earth.

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When you consider that the simulations sometimes need to be checked, tweaked, re-checked and run again hundreds of times, the value of a system that can replicate brain activity in real time becomes obvious.


Each of Neurogrid's 16 chips contains more than 65,000 silicon "neurons" whose activity can be programmed according to nearly 80 parameters, allowing the researchers to replicate the unique characteristics of different types of neurons. Soft-wired "synapses" crisscross the board, shuttling signals between every simulated neuron and the thousands of neurons it is networked with, effectively replicating the electrical chatter that constitutes communication in the brain.



The difference is that the computations that underlie whether or not a neuron fires are driven by continuous, non-linear processes, more akin to an analog signal. Neurogrid uses an analog signal for computations, and a digital signal for communication. In doing so, it follows the same hybrid analog-digital approach as the brain.

In addition to its superior simulations, it also uses a fraction of the energy of a supercomputer. For example, the Blue Gene/Q Sequoia consumes nearly 8 megawatts of electricity, enough to power over 160,000 homes. Eight megawatts at $0.10/kWh is $800 an hour, or a little over $7 million a year.

Neurogrid, on the other hand, operates on a paltry 5 watts, the amount of power used by a single cell phone charger.



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