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DTSTAMP:20260522T150123Z
LOCATION:Exhibit Hall B
DTSTART;TZID=America/Chicago:20181113T111500
DTEND;TZID=America/Chicago:20181113T120000
UID:submissions.supercomputing.org_SC18_sess224_inv103@linklings.com
SUMMARY:Brain-Inspired Massively-Parallel Computing
DESCRIPTION:Steve Furber (University of Manchester)\n\nNeuromorphic comput
 ing, that is, computing based upon brain-like principles - can be traced b
 ack to the pioneering work of Carver Mead in the 1980s. Academic research 
 into neuromorphic systems has continued since then in various forms, inclu
 ding analog, digital and hybrid systems, primarily with the objective of i
 mproving understanding of information processing in the brain. More recent
 ly, industrial neuromorphic systems have emerged - first the IBM TrueNorth
 , and then the Intel Loihi - with a greater focus on practical application
 s. In parallel, the last decade has seen an explosion of interest in less 
 brain-like, though still brain-inspired, artificial neural networks in mac
 hine learning applications that have, for example, placed high-quality spe
 ech recognition systems into everyday consumer use. However, these artific
 ial neural networks consume significant computer and electrical power, par
 ticularly during training, and there is strong interest in bringing these 
 requirements down and in enabling continuous on-line learning to take plac
 e in self-contained, mobile configurations. There is a growing expectation
 , so far unsubstantiated by compelling evidence, that neuromorphic technol
 ogies will have a role to play in delivering these efficiency gains. The S
 piNNaker (Spiking Neural Network Architecture) platform is an example of a
  highly flexible digital neuromorphic platform, based upon a massively-par
 allel configuration of small processors with a bespoke interconnect fabric
  designed to support the very high connectivity of biological neural nets 
 in real-time models. Although designed primarily to support brain science,
  it can also be used to explore more applications-oriented research.\n\nRe
 gistration Category: Tech Program Reg Pass, Exhibits Reg Pass\n\nSession C
 hair: Elizabeth Jessup (University of Colorado)\n\n
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