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DTSTART;TZID=Europe/Stockholm:20230627T113000
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UID:submissions.pasc-conference.org_PASC23_sess149_msa110@linklings.com
SUMMARY:Bringing GENE to GPUs: A Journey to Portability and Performance
DESCRIPTION:Minisymposium\n\nTilman Dannert (Max Planck Computing and Data
  Facility), Kai Germaschewski (University of New Hampshire), Bryce Allen (
 University of Chicago), and Gabriele Merlo (University of Texas at Austin)
 \n\nGENE is a widely-used simulation code for core plasma turbulence in fu
 sion devices. It is used for many years on nearly all available high perfo
 rmance computing systems. Since the advent of GPU-based systems, the code 
 has been reworked to leverage the great computing power of these accelerat
 ors. In this talk our porting way with pitfalls and successes will be pres
 ented. Two guiding principles led us through the process, first to keep th
 e low-level implementation of the GPU code separated from the physics impl
 ementations of the equations and second to keep the implementations as por
 table as possible across upcoming devices, namely from NVIDIA, AMD and Int
 el. Being a modern Fortran code, the usage of all kinds of C++ frameworks 
 seems to be at least complicated, we therefore decided to use a self-writt
 en mid-layer abstracting the creation of kernels and some numerical librar
 ies (FFT, BLAS). Similarly we implemented a data model that also uses seve
 ral backends for the different hardware architectures. This approach led t
 o fast progress in porting and still reasonable performance.\n\nDomain: Ph
 ysics\n\nSession Chair: Gilles Fourestey (EPFL)
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