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DTSTAMP:20260522T150110Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181114T083000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess323_post142@linklings.com
SUMMARY:Sol: Transparent Neural Network Acceleration Platform
DESCRIPTION:Nicolas Weber (NEC Laboratories Europe, NEC Corporation)\n\nWi
 th the usage of neural networks in a wide range of application fields, the
  necessity to execute these efficiently on high performance hardware is on
 e of the key problems for artificial intelligence (AI) framework providers
 . More and more new specialized hardware types and corresponding libraries
  appear from various manufacturers. The biggest problem arising is that th
 ese libraries usually are only supported by a very limited set of AI frame
 works and interoperability can become an issue. In this extended abstract 
 we present Sol, a transparent middleware for neural network acceleration. 
 Sol comes with an optimizing compiler engine, allowing to use device speci
 fic libraries and to implement own optimizations, that can be leveraged on
  all target devices. In contrast to other projects Sol explicitly aims at 
 optimizing prediction and training of neural networks.\n\nRegistration Cat
 egory: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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