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DTSTART;TZID=America/Denver:20231113T121200
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UID:submissions.supercomputing.org_SC23_sess441_ws_p3hpc104@linklings.com
SUMMARY:Many Cores, Many Models:  GPU Programming Model vs. Vendor Compati
 bility Overview
DESCRIPTION:Andreas Herten (Forschungszentrum Jülich; Juelich Supercomputi
 ng Centre (JSC), Institute for Advanced Simulation)\n\nIn recent history, 
 GPUs became a key driver of compute performance in HPC. With the installat
 ion of the Frontier supercomputer, they became the enablers of the exascal
 e era; further largest-scale installations are in progress (Aurora, El Cap
 itan, JUPITER). But the early-day dominance by NVIDIA and their CUDA progr
 amming model has changed: The current HPC GPU landscape features three ven
 dors (AMD, Intel, NVIDIA), each with native and derived programming models
 . The choices are ample, but not all models are supported on all platforms
 , especially if support for Fortran is needed; in addition, some restricti
 ons might apply. It is hard for scientific programmers to navigate this ab
 undance of choices and limits.  This presentation gives a guide by matchin
 g the GPU platforms with supported programming models, presented in a conc
 ise table and further elaborated in detailed comments. An assessment is ma
 de regarding the level of support of a model on a platform.\n\nTag: Perfor
 mance Measurement, Modeling, and Tools, Performance Optimization\n\nRegist
 ration Category: Workshop Reg Pass\n\nSession Chairs: Judith C. Hill (Lawr
 ence Livermore National Laboratory (LLNL)), CJ Newburn (NVIDIA Corporation
 ), Scott J. Parker (Argonne National Laboratory (ANL)), and John Pennycook
  (Intel Corporation)\n\n
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