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DTSTAMP:20240116T191659Z
LOCATION:DEF Concourse
DTSTART;TZID=America/Denver:20231114T100000
DTEND;TZID=America/Denver:20231114T170000
UID:submissions.supercomputing.org_SC23_sess289_spostg106@linklings.com
SUMMARY:Case Study for Performance Portability of GPU Programming Framewor
 ks for Hemodynamic Simulations
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nAristotle Martin (
 Duke University)\n\nPreparing for the deployment of large scientific and e
 ngineering codes on GPU-dense exascale systems is made challenging by the 
 unprecedented diversity of vendor hardware and programming model alternati
 ves for offload acceleration. To leverage the exaflops of GPUs from Fronti
 er (AMD) and Aurora (Intel), users of high performance computing (HPC) leg
 acy codes originally written to target NVIDIA GPUs will have to make decis
 ions with implications regarding porting effort, performance, and code mai
 ntainability. To facilitate HPC users navigating this space, we have estab
 lished a pipeline that combines generalized GPU performance models with pr
 oxy applications to evaluate the performance portability of a massively pa
 rallel computational fluid dynamics (CFD) code in CUDA, SYCL, HIP, and Kok
 kos with backends on current NVIDIA-based machines as well as testbeds for
  Aurora (Intel) and Frontier (AMD). We demonstrate the utility of predicti
 ve models and proxy applications in gauging performance bounds and guiding
  hand-tuning efforts.\n\nRegistration Category: Tech Program Reg Pass, Exh
 ibits Reg Pass
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