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A GPU implementation for improved granular simulations with LAMMPS

Emmanuel N. Millan, Christian Ringl, Carlos S. Bederian, Maria Fabiana Piccoli, Carlos Garcia Garino, Herbert M. Urbassek, Eduardo M. Bringa
CONICET, Mendoza
VI Latin American Symposium on High Performance Computing (HPCLatAm), 2013

@article{millan2013gpu,

   title={A GPU implementation for improved granular simulations with LAMMPS.},

   author={Mill{‘a}n, Emmanuel N and Ringl, Christian and Bederi{‘a}n, Carlos S and Piccoli, Mar{i}a Fabiana and Garino, Carlos Garc{i}a and Urbassek, Herbert M and Bringa, Eduardo M},

   year={2013}

}

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Granular mechanics plays an important role in many branches of science and engineering, from astrophysics applications in planetary and interstellar dust clouds, to processing of industrial mixtures and powders. In this context, a granular simulation model with improved adhesion and friction, is implemented within the open source code LAMMPS (lammps.sandia.gov). The performance of this model is tested in both CPU and GPU (Graphics Processing Unit) clusters, comparing with performance for the LAMMPS implementation of another often used interaction model, the Lennard-Jones potential. Timing shows accelerations of ~4-10x for GPUs versus CPUs, with good parallel scaling in a hybrid GPU-CPU cluster.
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