Enabling particle applications for exascale computing platforms

@article{Mniszewski2021EnablingPA,
  title={Enabling particle applications for exascale computing platforms},
  author={Susan M. Mniszewski and J. F. Belak and Jean-Luc Fattebert and Christian F. A. Negre and Stuart R. Slattery and Adetokunbo Adedoyin and Robert Francis Bird and Choongseok Chang and Guangye Chen and St{\'e}phane Ethier and Shane Fogerty and Salman Habib and Christoph Junghans and Damien Lebrun-Grandi{\'e} and Jamaludin Mohd-Yusof and Stan Gerald Moore and Daniel Osei-Kuffuor and Steven J. Plimpton and Adrian Pope and Samuel Temple Reeve and L. F. Ricketson and Aaron Scheinberg and Amil Y Sharma and Michael E. Wall},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.09056}
}
The Exascale Computing Project (ECP) is invested in co-design to assure that key applications are ready for exascale computing. Within ECP, the Co-design Center for Particle Applications (CoPA) is addressing challenges faced by particle-based applications across four “sub-motifs”: short-range particle–particle interactions (e.g., those which often dominate molecular dynamics (MD) and smoothed particle hydrodynamics (SPH) methods), long-range particle–particle interactions (e.g., electrostatic… Expand
Machine learning accelerated particle-in-cell plasma simulations
Particle-In-Cell (PIC) methods are frequently used for kinetic, high-fidelity simulations of plasmas. Implicit formulations of PIC algorithms feature strong conservation properties, up to numericalExpand

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