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DTSTART:19700308T020000
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DTSTAMP:20230124T171527Z
LOCATION:C146
DTSTART;TZID=America/Chicago:20221113T133000
DTEND;TZID=America/Chicago:20221113T141500
UID:submissions.supercomputing.org_SC22_sess424_misc123@linklings.com
SUMMARY:Invited Talk: Hybrid AI/HPC Approaches for Next Generation Multi-T
 rillion-Parameter Models
DESCRIPTION:Workshop\n\nInvited Talk: Hybrid AI/HPC Approaches for Next Ge
 neration Multi-Trillion-Parameter Models\n\nBrown\n\nWe live in a world wh
 ere large-scale systems for machine intelligence are increasingly being us
 ed to solve complex problems in scientific research. A convergence of mach
 ine learning model adoption alongside classical algorithms, purpose-built 
 scale-out systems availability in the cloud and maturing software ecosyste
 ms is paving the way for an exponential increase in the size of ML models 
 being deployed at scale by research institutions. Models with trillions of
  parameters are not too far out in the future. New hybrid systems combinin
 g both classical and AI approaches will be required to meet the needs of t
 hese large-scale algorithms.\n\nIn this session, Graphcore will reveal how
  Intelligence Processing Unit (IPU) systems, purpose built for AI and part
 icularly well suited to hybrid AI/HPC workloads, have been designed to tac
 kle these compute scale-out challenges. This technology allows researchers
  to start small and then seamlessly scale to tackle mega-models, preparing
  them for the multi-trillion-parameter model era.\n\nSession Format: Recor
 ded\n\nTag: Algorithms, Exascale Computing, Extreme Scale Computing, Heter
 ogeneous Systems, Post-Moore Computing, Quantum Computing\n\nRegistration 
 Category: Workshop Reg Pass
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