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DTSTART;TZID=America/Denver:20231116T133000
DTEND;TZID=America/Denver:20231116T150000
UID:submissions.supercomputing.org_SC23_sess192@linklings.com
SUMMARY:Scalable and Adaptable Architectures for AI/HPC Advancement
DESCRIPTION:Scalable and Adaptable Architectures for AI/HPC Advancement\n\
 nAI/Machine Learning usage is exploding in both application and model size
 . Predictive analytics, physics, modeling, and new use cases for generativ
 e AI/ML are increasing model sizes by 10x every 18 months. The custom proc
 essors and accelerators used for AI/ML require continually higher I/O band
 width...\n\n\nKeren Bergman (Columbia University); John Shalf (Lawrence Be
 rkeley National Laboratory (LBNL)); Sadaf Alam (University of Bristol); Vl
 adimir Stojanovic (University of California, Berkeley; Ayar Labs); Sergey 
 Shumaray (Intel Corporation); Larry Dennison (NVIDIA Corporation); and Viv
 ek Raghunathan (Xscape Photonics)\n\nTag: Artificial Intelligence/Machine 
 Learning\n\nRegistration Category: Tech Program Reg Pass\n\nSession Chair:
  Keren Bergman (Columbia University, Ayar Labs)
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