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==Abstract==
  
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Particle-In-Cell (PIC) methods such as the Material Point Method (MPM)
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can be cast in formulations suitable to the requirements of data locality and fine-grained
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parallelism of modern hardware accelerators such as Graphics Processing Units (GPUs).
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While continuum mechanics simulations have already shown the capabilities of MPM on
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a wide range of phenomena, the use of the method in compressible gas dynamics is less
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frequent. This contribution aims to show the potential of a GPU-based MPM parallel
 +
implementation for compressible fluid dynamics, as well as to assess the reliability of this
 +
approach in reproducing supersonic gas flows against solid obstacles. The results in the
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paper represent a stepping stone towards a highly parallel, Multi-GPU, MPM-base solver
 +
for M ach > 1 Fluid-Structure Interaction problems.

Revision as of 17:00, 23 November 2023

Abstract

Particle-In-Cell (PIC) methods such as the Material Point Method (MPM) can be cast in formulations suitable to the requirements of data locality and fine-grained parallelism of modern hardware accelerators such as Graphics Processing Units (GPUs). While continuum mechanics simulations have already shown the capabilities of MPM on a wide range of phenomena, the use of the method in compressible gas dynamics is less frequent. This contribution aims to show the potential of a GPU-based MPM parallel implementation for compressible fluid dynamics, as well as to assess the reliability of this approach in reproducing supersonic gas flows against solid obstacles. The results in the paper represent a stepping stone towards a highly parallel, Multi-GPU, MPM-base solver for M ach > 1 Fluid-Structure Interaction problems.

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Document information

Published on 23/11/23
Submitted on 23/11/23

Volume The Material Point Method – Recent Advances, 2023
DOI: 10.23967/c.particles.2023.026
Licence: CC BY-NC-SA license

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