title: Convolutional networks for fast, energy-efficient neuromorphic computing.
abstract: Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. 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.
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120 sesser@us.ibm.com.
authors.forename: Steven K
authors.initials: SK
authors.lastname: Esser
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Paul A
authors.initials: PA
authors.lastname: Merolla
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: John V
authors.initials: JV
authors.lastname: Arthur
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Cassidy
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Rathinakumar
authors.initials: R
authors.lastname: Appuswamy
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Alexander
authors.initials: A
authors.lastname: Andreopoulos
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: David J
authors.initials: DJ
authors.lastname: Berg
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Jeffrey L
authors.initials: JL
authors.lastname: McKinstry
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Timothy
authors.initials: T
authors.lastname: Melano
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Davis R
authors.initials: DR
authors.lastname: Barch
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Carmelo
authors.initials: C
authors.lastname: di Nolfo
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Pallab
authors.initials: P
authors.lastname: Datta
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Arnon
authors.initials: A
authors.lastname: Amir
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Brian
authors.initials: B
authors.lastname: Taba
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Myron D
authors.initials: MD
authors.lastname: Flickner
authors.affiliation: Brain-Inspired Computing, IBM Research-Almaden, San Jose, CA 95120.
authors.forename: Dharmendra S
authors.initials: DS
authors.lastname: Modha
keywords: TrueNorth; convolutional network; neural network; neuromorphic