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DTSTAMP:20181221T160726Z
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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:Workshop\nDiversity, Education, Hot Topics, Workshop Reg Pass\
 n\nUse Cases of Neuromorphic Co-Processors in Future HPC Environments\n\nS
 chuman\n\nWith the looming end of Moore’s law and the end of Dennard scali
 ng, the HPC community is exploring the use of specialized hardware as acce
 lerators for certain tasks. Neuromorphic computing is a field in which neu
 ral networks are implemented in hardware to achieve intelligent computatio
 n with lower power and on a smaller footprint than traditional von Neumann
  architectures.  Neuromorphic systems are compelling candidates for inclus
 ion as co-processors in future HPCs, and they are suitable as co-processor
 s for multiple types of applications.  Here, we discuss neuromorphic syste
 ms as machine learning and graph algorithm accelerators.   As more users a
 re exposed to neuromorphic systems, we anticipate that even more use cases
  will arise.
URL:https://sc18.supercomputing.org/presentation/?id=ws_whpc113&sess=sess1
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