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ABSTRACT
This paper describes the hardware and software ecosystem encompassing the brain-inspired TrueNorth processor – a 70mW reconfigurable silicon chip with 1 million neurons, 256 million synapses, and 4096 parallel and distributed neural cores. For systems, we present a scale-out system loosely coupling 16 single-chip boards and a scale-up system tightly integrating 16 chips in a 4 × 4 configuration by exploiting TrueNorth's native tiling. For software, we present an end-to-end ecosystem consisting of a simulator, a programming language, an integrated programming environment, a library of algorithms and applications, firmware, tools for deep learning, a teaching curriculum, and cloud enablement. For the scale-up systems we summarize our approach to physical placement of neural network, to reduce intra- and inter-chip network traffic. The ecosystem is in use at over 30 universities and government/corporate labs. Our platform is a substrate for a spectrum of applications from mobile and embedded computing to cloud and supercomputers.
INDEX TERMS
Biological neural networks, Ecosystems, Neurons, Hardware, Software, Training, Computer architecture
CITATION

J. Sawada et al., "TrueNorth Ecosystem for Brain-Inspired Computing: Scalable Systems, Software, and Applications," SC16: International Conference for High Performance Computing, Networking, Storage and Analysis(SC), Salt Lake City, UT, USA, 2016, pp. 130-141.
doi:10.1109/SC.2016.11
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