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DTSTART;TZID=America/Chicago:20181111T144800
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UID:submissions.supercomputing.org_SC18_sess160_ws_whpc113@linklings.com
SUMMARY:Use Cases of Neuromorphic Co-Processors in Future HPC Environments
DESCRIPTION:Catherine Schuman (Oak Ridge National Laboratory)\n\nWith the 
 looming end of Moore’s law and the end of Dennard scaling, the HPC communi
 ty is exploring the use of specialized hardware as accelerators for certai
 n tasks. Neuromorphic computing is a field in which neural networks are im
 plemented in hardware to achieve intelligent computation with lower power 
 and on a smaller footprint than traditional von Neumann architectures.  Ne
 uromorphic systems are compelling candidates for inclusion as co-processor
 s in future HPCs, and they are suitable as co-processors for multiple type
 s of applications.  Here, we discuss neuromorphic systems as machine learn
 ing and graph algorithm accelerators.   As more users are exposed to neuro
 morphic systems, we anticipate that even more use cases will arise.\n\nTag
 : Diversity, Education, Hot Topics\n\nRegistration Category: Workshop Reg 
 Pass\n\nSession Chairs: Toni Collis (Women in High Performance Computing);
  Weronika Filinger (Edinburgh Parallel Computing Centre (EPCC); University
  of Edinburgh, Scotland); and Misbah Mubarak (Amazon Web Services)\n\n
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