Journal ArticleDOI
A million spiking-neuron integrated circuit with a scalable communication network and interface
Paul A. Merolla,John V. Arthur,Rodrigo Alvarez-Icaza,Andrew S. Cassidy,Jun Sawada,Filipp Akopyan,Bryan L. Jackson,Nabil Imam,Chen Guo,Yutaka Nakamura,Bernard Brezzo,Ivan Vo,Steven K. Esser,Rathinakumar Appuswamy,Brian Taba,Arnon Amir,Myron D. Flickner,William P. Risk,Rajit Manohar,Dharmendra S. Modha +19 more
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TLDR
Inspired by the brain’s structure, an efficient, scalable, and flexible non–von Neumann architecture is developed that leverages contemporary silicon technology and is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification.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.read more
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Journal ArticleDOI
Fully memristive neural networks for pattern classification with unsupervised learning
Zhongrui Wang,Saumil Joshi,Sergey Savel'ev,Wenhao Song,Rivu Midya,Yunning Li,Mingyi Rao,Peng Yan,Shiva Asapu,Ye Zhuo,Hao Jiang,Peng Lin,Can Li,Jung Ho Yoon,Navnidhi K. Upadhyay,Jiaming Zhang,Miao Hu,John Paul Strachan,Mark Barnell,Qing Wu,Huaqiang Wu,R. Stanley Williams,Qiangfei Xia,Jianhua Yang +23 more
TL;DR: It is shown that a diffusive memristor based on silver nanoparticles in a dielectric film can be used to create an artificial neuron with stochastic leaky integrate-and-fire dynamics and tunable integration time, which is determined by silver migration alone or its interaction with circuit capacitance.
Proceedings ArticleDOI
Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing
TL;DR: In this paper, a set of optimization techniques to minimize performance loss in the conversion process for convolutional networks and fully connected deep networks are presented, which yield networks that outperform all previous SNNs on the MNIST database.
Journal ArticleDOI
Neuro-Inspired Computing With Emerging Nonvolatile Memorys
TL;DR: This comprehensive review summarizes state of the art, challenges, and prospects of the neuro-inspired computing with emerging nonvolatile memory devices and presents a device-circuit-algorithm codesign methodology to evaluate the impact of nonideal device effects on the system-level performance.
Journal ArticleDOI
Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.
Bodo Rueckauer,Iulia-Alexandra Lungu,Yuhuang Hu,Michael Pfeiffer,Michael Pfeiffer,Shih-Chii Liu +5 more
TL;DR: This paper shows conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset.
Journal ArticleDOI
Convolutional networks for fast, energy-efficient neuromorphic computing
Steven K. Esser,Paul A. Merolla,John V. Arthur,Andrew S. Cassidy,Rathinakumar Appuswamy,Alexander Andreopoulos,David Berg,Jeffrey L. McKinstry,Timothy Melano,R Davis,Carmelo di Nolfo,Pallab Datta,Arnon Amir,Brian Taba,Myron D. Flickner,Dharmendra S. Modha +15 more
TL;DR: This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.
References
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Journal ArticleDOI
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
David H. Hubel,Torsten N. Wiesel +1 more
TL;DR: This method is used to examine receptive fields of a more complex type and to make additional observations on binocular interaction and this approach is necessary in order to understand the behaviour of individual cells, but it fails to deal with the problem of the relationship of one cell to its neighbours.
Journal ArticleDOI
Can programming be liberated from the von Neumann style?: a functional style and its algebra of programs
TL;DR: A new class of computing systems uses the functional programming style both in its programming language and in its state transition rules; these systems have semantics loosely coupled to states—only one state transition occurs per major computation.
Journal ArticleDOI
Object vision and spatial vision: two cortical pathways
TL;DR: Evidence is reviewed indicating that striate cortex in the monkey is the source of two multisynaptic corticocortical pathways, one of which enables the visual identification of objects and the other allows instead the visual location of objects.
Journal ArticleDOI
Modality and topographic properties of single neurons of cat's somatic sensory cortex.
TL;DR: Observations upon the modality and topographical attributes of single neurons of the first somatic sensory area of the cat’s cerebral cortex, the analogue of the cortex of the postcentral gyrus in the primate brain, support an hypothesis of the functional organization of this cortical area.
Journal ArticleDOI
Neuronal circuits of the neocortex
TL;DR: It is found that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought.
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