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DTSTART:19700308T020000
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DTSTAMP:20200129T163556Z
LOCATION:401-402-403-404
DTSTART;TZID=America/Denver:20191122T090500
DTEND;TZID=America/Denver:20191122T092000
UID:submissions.supercomputing.org_SC19_sess132_ws_p3hpc106@linklings.com
SUMMARY:Performance Portability of Multi-Material Kernels
DESCRIPTION:Workshop\n\nPerformance Portability of Multi-Material Kernels\
 n\nReguly\n\nTrying to improve performance, portability, and productivity 
 of an application presents non-trivial trade-offs, which are often difficu
 lt to quantify. Recent work has developed metrics for performance portabil
 ity, as well some aspects of productivity - in this case study, we present
  a set of challenging computational kernels and their implementations from
  the domain of multi-material simulations, and evaluate them using these m
 etrics. \n\nThree key kernels are implemented using OpenMP, OpenMP offload
 , OpenACC, CUDA,  SYCL, and KOKKOS, and tested on ARM ThunderX2, IBM Power
  9, Intel KNL, Broadwell, and Skylake CPUs, as well as NVIDIA P100 and V10
 0 GPUs. We also consider the choice of compilers, evaluating LLVM/Clang, G
 CC, PGI, Intel, IBM XL, and Cray compilers, where available. We present a 
 detailed performance analysis, calculate performance portability and code 
 divergence metrics, contrasting performance, portability, and productivity
 .\n\nTag: Workshop Reg Pass, Parallel Programming Languages, Libraries, an
 d Models, Performance, Portability, Productivity\n\nRegistration Category:
  Workshop Reg Pass, Parallel Programming Languages, Libraries, and Models,
  Performance, Portability, Productivity
URL:https://sc19.supercomputing.org/presentation/?id=ws_p3hpc106&sess=sess
 132
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