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Science. 2014 Aug 8;345(6197):668-73. doi: 10.1126/science.1254642. Epub 2014 Aug 7.

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

Author information

1
IBM Research-Almaden, 650 Harry Road, San Jose, CA 95120, USA.
2
IBM Research-Austin, 11501 Burnet Road, Austin, TX 78758, USA.
3
Cornell University, 358 Upson Hall, Ithaca, NY 14853 USA.
4
IBM Engineering and Technology Services, San Jose Design Center, 650 Harry Road, San Jose, CA 95120, USA.
5
IBM Research-Tokyo, Nippon Building Fund Toyosu Canal Front Building, 5-6-52 Toyosu, Koto-ku Tokyo 135-8511, Japan.
6
IBM T. J. Watson Research Center, 101 Kitchawan Road, Yorktown Heights, NY 10598, USA.
7
Cornell Tech, 111 Eighth Avenue No. 302, New York, NY 10011, USA.
8
IBM Research-Almaden, 650 Harry Road, San Jose, CA 95120, USA. dmodha@us.ibm.com.

Abstract

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts.

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PMID:
25104385
DOI:
10.1126/science.1254642
[Indexed for MEDLINE]
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