Computational & Technology Resources
an online resource for computational,
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Computational Science, Engineering & Technology Series
ISSN 1759-3158
CSETS: 40
ADVANCES IN PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING
Edited by: P. Iványi, B.H.V. Topping and G. Várady
Chapter 6

Simulation and Visualization of Discrete Particles on Clusters, Grids and Clouds

A. Kačeniauskas1 and R. Pacevič2

1Laboratory of Parallel Computing, Vilnius Gediminas Technical University, Vilnius, Lithuania
2Department of Graphical Systems, Vilnius Gediminas Technical University, Vilnius, Lithuania

Full Bibliographic Reference for this chapter
A. Kaceniauskas , R. Pacevic, "Simulation and Visualization of Discrete Particles on Clusters, Grids and Clouds", in P. Iványi, B.H.V. Topping and G. Várady, (Editors), "Advances in Parallel, Distributed, Grid and Cloud Computing for Engineering", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 6, pp 109-136, 2017. doi:10.4203/csets.40.6
Keywords: discrete particles, discrete element method, domain decomposition, visualization of cracks, cloud computing, Docker containers..

Abstract
This paper presents the development of parallel algorithms and visualization techniques for particle systems simulated by the discrete element method on clusters, grids and clouds. The dynamic domain decomposition strategies based on the moving planes, the multilevel k-way graph-partitioning and the recursive coordinate bisection were applied to the simulation of hopper discharge. The parallel speedup of discrete element computations measured on Docker containers of the OpenStack cloud was compared with that obtained by using the native hardware. The cell cut-, Voronoiand cell centre-based techniques were developed for extraction and visualization of crack surfaces propagating in monodispersed particulate media, which was simulated by the discrete element method. The quantitative comparison of three visualization techniques based on local space decompositions was performed. The trials from the case study showed that the developed parallel algorithms and visualization techniques were able to satisfy needs of researchers simulating large discrete particle systems.

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