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DTSTAMP:20260422T000711Z
LOCATION:601
DTSTART;TZID=America/Denver:20231112T090100
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UID:submissions.supercomputing.org_SC23_sess426_ws_llvmf101@linklings.com
SUMMARY:OpenMP Kernel Language Extensions for Performance Portable GPU Cod
 es
DESCRIPTION:Shilei Tian (Stony Brook University); Tom Scogland (Lawrence L
 ivermore National Laboratory (LLNL)); Barbara Chapman (Stony Brook Univers
 ity, Hewlett Packard Enterprise (HPE)); and Johannes Doerfert (Lawrence Li
 vermore National Laboratory (LLNL))\n\nIn this work, we introduce extensio
 ns to LLVM OpenMP, transforming it into a versatile and performance portab
 le kernel language for GPU programming.  These extensions allow for the se
 amless porting of programs written in kernel languages to high-performance
  OpenMP GPU programs with minimal modifications.  To evaluate our extensio
 n, we implemented a proof-of-concept prototype that contains a subset of e
 xtensions we proposed.  We ported six established CUDA proxy and benchmark
  applications and evaluated their performance on both AMD and NVIDIA platf
 orms.  By comparing with native versions (HIP and CUDA), our results demon
 strate that OpenMP, augmented with our extensions, can not only match but 
 also in some cases exceed the performance of kernel languages, thereby off
 ering performance portability with minimal effort from application develop
 ers.\n\nTag: Compilers, Heterogeneous Computing, Performance Optimization\
 n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: James Brodm
 an (AMD); Ryan Kabrick (Tactical Computing Laboratories LLC, University of
  Delaware); Patrick S. McCormick (Los Alamos National Laboratory (LANL)); 
 and Alexis Perry-Holby (Los Alamos National Laboratory (LANL))\n\n
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