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DTSTART;TZID=America/Chicago:20251116T083000
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UID:submissions.supercomputing.org_SC25_sess252_tut113@linklings.com
SUMMARY:Efficient Distributed GPU Programming for Exascale
DESCRIPTION:Andreas Herten (Forschungszentrum Jülich, Jülich Supercomputin
 g Centre (JSC)); Simon Garcia de Gonzalo (Sandia National Laboratories); D
 avid Appelhans (NVIDIA Corporation); and Lena Oden (University of Hagen)\n
 \nOver the past decade, GPUs became ubiquitous in HPC installations around
  the world, delivering the majority of performance of some of the largest 
 supercomputers, steadily increasing the available compute capacity. Finall
 y, four exascale systems are deployed (Frontier, Aurora, El Capitan, JUPIT
 ER), using GPUs as the core computing devices for this era of HPC. To take
  advantage of these GPU-accelerated systems with tens of thousands of devi
 ces, application developers need to have the proper skills and tools to un
 derstand, manage, and optimize distributed GPU applications. In this tutor
 ial, participants will learn techniques to efficiently program large-scale
  multi-GPU systems. While programming multiple GPUs with MPI is explained 
 in detail, advanced tuning techniques and complementing programming models
  like NCCL and NVSHMEM are also presented. Tools for analysis are shown an
 d used to motivate and implement performance optimizations. The tutorial t
 eaches fundamental concepts that apply to GPU-accelerated systems of any v
 endor in general, taking the NVIDIA platform as an example. This tutorial 
 is a combination of lectures and hands-on exercises, using the JUPITER sys
 tem for interactive learning and discovery.\n\nRecording: Livestreamed, Re
 corded\n\nRegistration Category: Tutorial Reg Pass\n\n
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