File:DARPA SyNAPSE 16 Chip Board.jpg

A circuit board with 16 of the new brain-inspired chips in a 4×4 array along with interface hardware. The board is being used to rapidly analyze high-resolution images.

DARPA-funded researchers have developed one of the world’s largest and most complex computer chips ever produced—one whose architecture is inspired by the neuronal structure of the brain and requires only a fraction of the electrical power of conventional chips.

Designed by researchers at IBM in San Jose, California, under DARPA’s Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program, the chip has more than five billion transistors and boasts more than 250 million “synapses,” or programmable logic points, analogous to the connections between neurons in the brain. That’s still orders of magnitude fewer than the number of actual synapses in the brain, but a giant step toward making ultra-high performance, low-power neuro-inspired systems a reality.

Many tasks that people and animals perform effortlessly, such as perception and pattern recognition, audio processing and motor control, are difficult for traditional computing architectures to do without consuming a lot of power. Biological systems consume much less energy than current computers attempting the same tasks. The SyNAPSE program was created to speed the development of a brain-inspired chip that could perform difficult perception and control tasks while at the same time achieving significant energy savings.

The SyNAPSE-developed chip, which can be tiled to create large arrays, has one million electronic “neurons” and 256 million electronic synapses between neurons. Built on Samsung Foundry's 28nm process technology, the 5.4 billion transistor chip has one of the highest transistor counts of any chip ever produced. Each chip consumes less than 100 milliWatts of electrical power during operation. When applied to benchmark tasks of pattern recognition, the new chip achieved two orders of magnitude in energy savings compared to state-of-the-art traditional computing systems.