학술논문
TrueNorth Ecosystem for Brain-Inspired Computing: Scalable Systems, Software, and Applications
Document Type
Conference
Author
Sawada, J.; Akopyan, F.; Cassidy, A.S.; Taba, B.; Debole, M.V.; Datta, P.; Alvarez-Icaza, R.; Amir, A.; Arthur, J.V.; Andreopoulos, A.; Appuswamy, R.; Baier, H.; Barch, D.; Berg, D.J.; Di Nolfo, C.; Esser, S.K.; Flickner, M.; Horvath, T.A.; Jackson, B.L.; Kusnitz, J.; Lekuch, S.; Mastro, M.; Melano, T.; Merolla, P.A.; Millman, S.E.; Nayak, T.K.; Pass, N.; Penner, H.E.; Risk, W.P.; Schleupen, K.; Shaw, B.; Wu, H.; Giera, B.; Moody, A.T.; Mundhenk, N.; Van Essen, B.C.; Wang, E.X.; Widemann, D.P.; Wu, Q.; Murphy, W.E.; Infantolino, J.K.; Ross, J.A.; Shires, D.R.; Vindiola, M.M.; Namburu, R.; Modha, D.S.
Source
SC16: International Conference for High Performance Computing, Networking, Storage and Analysis SC High Performance Computing, Networking, Storage and Analysis, SC16: International Conference for. :130-141 Nov, 2016
Subject
Language
ISSN
2167-4337
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.