Transactions of the Japan Society for Computational Engineering and Science
Online ISSN : 1347-8826
ISSN-L : 1344-9443
GPU Acceleration Techniques for DEM Simulations of Granular Materials with Broad Particle Size Distribution
Daisuke NISHIURAHide SAKAGUCHI
Author information
JOURNALS FREE ACCESS

2010 Volume 2010 Pages 20100008

Details
Abstract

New algorithms were developed to implement the high-performance discrete element method (DEM) on a graphics processing unit (GPU) for simulating particle systems with a broad particle size distribution. First, we focused on minimizing the usage of GPU memory required to construct a table that allows reference to the interparticle contact force; this memory usage had increased drastically with an increase in the width of the particle size distribution. As a result, the memory usage during GPU computing remains almost constant irrespective of the width of the particle size distribution. Second, we improved our previous method for generating a list of contact candidate pairs; the particle label was sorted according to not only the cell label but also the particle size. The searching method for adjacent cells was improved by using a reordered particle label because the number of memory accesses could be reduced by preventing the search for neighboring particles that are impossible to contact. By using the developed algorithms, we investigated the effects of cell size, particle size ratio, and number of particle size components on the computational efficiency. The total computational speed of the DEM increased with an increase in the number of components in the particle size distribution; however, the computational efficiency deteriorated with an increase in the particle size ratio. In addition, we confirmed that the optimum cell size changed in accordance with the particle size distribution. Thus, we showed that the new algorithms can be used to improve the computational efficiency of the DEM on a GPU for particles with a broad particle size distribution with preventing the waste of GPU memory usage.

Information related to the author
© 2010 The Japan Society For Computational Engineering and Science
Previous article Next article
feedback
Top