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Neuromorphic computing gets ready for the (really) big time

Published:01 June 2014Publication History
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Abstract

A technology inspired by biological principles but 'steamrolled for decades' prepares to take off as Moore's Law approaches its long-anticipated end.

References

  1. "A New Era of Computing Requires a New Way to Program Computers," Dharmendra S. Modha, http://bit.ly/1i2rxqhGoogle ScholarGoogle Scholar
  2. "Low-Power Chips to Model a Billion Neurons," Steve Furber, IEEE Spectrum, August 2012, http://bit.ly/1fuotGvGoogle ScholarGoogle Scholar
  3. "Cognitive Computing," Dharmendra S. Modha, Rajagopal Ananthanarayanan, Steven K. Esser, Anthony Ndirango, Anthony J. Sherbondy, Raghavendra Singh, CACM, August 2011, http://bit.ly/1i2rtqzGoogle ScholarGoogle Scholar
  4. "A Computer that Works like the Human Brain," a TEDx talk with bioengineer Kwabena Boahen, http://bit.ly/1gOY0UMGoogle ScholarGoogle Scholar

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  1. Neuromorphic computing gets ready for the (really) big time

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      Mohammed Ziaur Rahman

      Some global initiatives to build a biologically inspired computer are highlighted in this article. The term “neuromorphic” is used to refer to biologically inspired computing as a whole, and specifically to analog circuits for neural network implementations. The Defense Advanced Research Projects Agency (DARPA)-funded Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) and the Neurogrid project at Stanford University, both US initiatives, are highlighted before referring to a commercial initiative by Qualcomm. The research goals vary from implementation of a few hundred to billions of neurons to the development of analog neuromorphic systems. Apart from physical implementation, software remains the most critical component for the success of these systems. The task is to rethink programming and algorithms for fitting into these systems. Therefore, researchers are collaborating to develop a neural compiler that will enable developers to move their proven algorithms to the new architecture. From the industry side, Qualcomm's neural core processor Zeroth is reported. It aims “to bring the sort of intelligence that people usually associate with the cloud down to the handset.” Two projects from the European Union's billion-euro Human Brain Project (HBP) are highlighted. The first one is SpiNNaker (Spiking Neural Network Architecture) from the University of Manchester. It is completely digital and connects ARM cores in a massively parallel network whose ultimate aim is to connect a million cores for brain research purposes. The second one is a neuromorphic project from the University of Heidelberg. It is focused on using mixed-signal neurons “to reduce the need to drive off-chip interconnections.” Can these projects bring more successes than their predecessors, “the artificial neural networks of a quarter century ago”__?__ This article both raises the question and gives an indirect answer. Online Computing Reviews Service

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      • Published in

        cover image Communications of the ACM
        Communications of the ACM  Volume 57, Issue 6
        June 2014
        103 pages
        ISSN:0001-0782
        EISSN:1557-7317
        DOI:10.1145/2602695
        • Editor:
        • Moshe Y. Vardi
        Issue’s Table of Contents

        Copyright © 2014 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 June 2014

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