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DTSTAMP:20260422T000711Z
LOCATION:710
DTSTART;TZID=America/Denver:20231113T144000
DTEND;TZID=America/Denver:20231113T150000
UID:submissions.supercomputing.org_SC23_sess445_ws_scalah105@linklings.com
SUMMARY:Optimization of Ported CFD Kernels on Intel Data Center GPU Max 15
 50 Using oneAPI ESIMD
DESCRIPTION:Mohammad Zubair (Old Dominion University); Aaron Walden, Gabri
 el Nastac, and Eric Nielsen (NASA Langley Research Center); and Christoph 
 Bauinger and Xiao Zhu (Intel Corporation)\n\nWe describe our experience po
 rting FUN3D's CUDA-optimized kernels to Intel oneAPI SYCL. We faced severa
 l challenges, including the suboptimal performance of the oneAPI code on I
 ntel's new data center GPU. The suboptimal performance of the oneAPI code 
 was due  to high register spills, memory latency, and poor vectorization. 
 We addressed these issues by implementing the kernels using Intel oneAPI's
  Explicit SIMD SYCL extension (ESIMD) API. The ESIMD API enables the writi
 ng of explicitly vectorized kernel code, gives more precise control over r
 egister usage and prefetching, and better handles thread divergence compar
 ed to SYCL. The ESIMD code outperforms the optimized SYCL code by up to a 
 factor of 3.6, depending on the kernel. We also compared the performance w
 ith the CUDA-optimized version on NVIDIA V100 and A100 GPUs. We found the 
 performance of a single tile of the Intel GPU using ESIMD greater than NVI
 DIA V100 and similar to NVIDIA A100.\n\nTag: Algorithms, Heterogeneous Com
 puting, Large Scale Systems\n\nRegistration Category: Workshop Reg Pass\n\
 nSession Chairs: Vassil Alexandrov (Hartree Centre, STFC); Jack Dongarra (
 University of Tennessee, Knoxville; Oak Ridge National Laboratory (ORNL));
  Christian Engelmann (Oak Ridge National Laboratory (ORNL)); Al Geist (Oak
  Ridge National Laboratory (ORNL)); and Dieter A. Kranzlmueller (Ludwig-Ma
 xmilians-Universität München, Leibniz Supercomputing Centre (LRZ))\n\n
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