DMCA
A parallel adaptive mesh refinement algorithm for solving nonlinear dynamical systems
| Venue: | Int. J. High Perform. Comput. Appl |
| Citations: | 1 - 0 self |
BibTeX
@ARTICLE{Huang_aparallel,
author = {Weicheng Huang and Danesh K. Tafti and Weicheng Huang and Danesh K. Tafti},
title = {A parallel adaptive mesh refinement algorithm for solving nonlinear dynamical systems},
journal = {Int. J. High Perform. Comput. Appl},
year = {},
volume = {18},
pages = {2004}
}
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Abstract
An unstructured adaptive mesh refinement (AMR) method is used in conjunction with the cell-to-cell mapping method for solving nonlinear dynamical systems. The global analysis is initiated with a coarse mesh without any a priori knowledge of the cell state space of the system. The process of investigation of nonlinear systems is improved through an iterative cell refinement and cell lumping process. In this paper, a parallel algorithm for the AMR procedure is developed using a shared memory programming paradigm. In addition, the concept of dynamic computing for better resource management is introduced. The approach compensates for changes in the computing workload by dynamically allocating/deallocating shared memory threads for more efficient computations. Results on the SGI Origin
Keyphrases
nonlinear dynamical system parallel adaptive mesh refinement algorithm priori knowledge iterative cell refinement parallel algorithm amr procedure coarse mesh efficient computation shared memory resource management sgi origin nonlinear system memory thread unstructured adaptive mesh refinement cell-to-cell mapping method cell state space global analysis
