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DTSTART;TZID=Europe/Stockholm:20230626T173000
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UID:submissions.pasc-conference.org_PASC23_sess154_msa217@linklings.com
SUMMARY:Unleashing the Power of Multiple GPUs for ECsim Using OpenACC
DESCRIPTION:Minisymposium\n\nNitin Shukla (CINECA), Elisabetta Boella (Lan
 caster University), Maria Elena Innocenti (Ruhr University Bochum), Matt B
 ettencourt and Mozhgan Kabiri Chimeh (NVIDIA Inc.), Giovanni Lapenta (KU L
 euven), and Filippo Spiga (NVIDIA Inc.)\n\nThe Particle-In-Cell (PIC) meth
 od is a particle-mesh technique widely used to model the kinetic nature of
  plasmas. Macroparticles representative of several plasma particles intera
 ct via electromagnetic fields that they produce. These fields are calculat
 ed by solving Maxwell's equations on a fixed grid, where source terms are 
 obtained by interpolating the particles to the grid. This presentation foc
 uses on the massively parallel PIC code ECsim. The peculiarity of ECsim is
  that both Maxwell’s equations for the fields and motion equations for the
  particles are discretised implicitly in time and the scheme is energy con
 serving. This makes the code stable and accurate for a large range of spat
 ial and temporal resolutions. We will review our recent effort to prepare 
 the code for future exascale architectures. We will describe the implement
 ation of OpenACC directives and the memory management technique that we ad
 opted to port particle kernels on GPUs. For typical numerical parameters t
 hat we employ in our simulations, this allows us to gain a 5x speedup with
  respect to the CPU version of the code. Finally, we will discuss code per
 formance on different generations of NVIDIA GPUs and scaling tests of the 
 code on different supercomputers.\n\nDomain: Engineering\n\nSession Chair:
  Jeremy Johnathan Williams (KTH Royal Institute of Technology)
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