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DTSTART:19700308T020000
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DTSTAMP:20250822T115805Z
LOCATION:Room 5.0B15 & 16
DTSTART;TZID=Europe/Stockholm:20250618T120000
DTEND;TZID=Europe/Stockholm:20250618T123000
UID:submissions.pasc-conference.org_PASC25_sess171_pap115@linklings.com
SUMMARY:An Efficient GPU Parallelization Strategy for Binary Collisions in
  Particle-In-Cell Plasma Simulations
DESCRIPTION:Remi Lehe and Muhammad Haseeb (Lawrence Berkeley National Labo
 ratory); Justin Angus and David Grote (Lawrence Livermore National Laborat
 ory); Roelof Groenewald (TAE); and Arianna Formenti, Axel Huebl, Jack Desl
 ippe, and Jean-Luc Vay (Lawrence Berkeley National Laboratory)\n\nThe Part
 icle-In-Cell (PIC) algorithm coupled with binary collision modules is a wi
 dely applicable method to simulate plasmas over a broad range of regimes (
 from the collisionless kinetic regime to the collisional regime). While se
 veral popular PIC codes implement binary collision modules, their performa
 nce on GPUs can be constrained by the default parallelization strategy, wh
 ich assigns one GPU thread per simulation cell. This approach can underuti
 lize GPU resources for simulations with many macroparticles per cell, and 
 relatively few cells per GPU. To address this limitation, we propose an al
 ternative parallelization strategy that instead GPU distributes threads ba
 sed on independent pairs of colliding particles. Our proposed strategy sho
 ws a speed improvement of up to $\sim 4 \times$ for cases with relatively 
 few cells per GPU and a similar performance otherwise.\n\nDomain: Engineer
 ing, Physics, Computational Methods and Applied Mathematics\n\nSession Cha
 ir: Andreas Lintermann (Forschungszentrum Jülich GmbH)\n\n
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