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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 9, 2019.
Abstract: The fourth-order finite difference Iterative Alternating Decomposition Explicit Method of Mitchell and Fairweather (IADEMF4) sequential algorithm has demonstrated its ability to perform with high accuracy and efficiency for the solution of a one-dimensional heat equation with Dirichlet boundary conditions. This paper develops the parallelization of the IADEMF4, by applying the Red-Black (RB) ordering technique. The proposed IADEMF4-RB is implemented on multiprocessor distributed memory architecture based on Parallel Virtual Machine (PVM) environment with Linux operating system. Numerical results show that the IADEMF4-RB accelerates the convergence rate and largely improves the serial time of the IADEMF4. In terms of parallel performance evaluations, the IADEMF4-RB significantly outperforms its counterpart of the second-order (IADEMF2-RB), as well as the benchmarked fourth-order classical iterative RB methods, namely, the Gauss-Seidel (GS4-RB) and the Successive Over-relaxation (SOR4-RB) methods.
Noreliza Abu Mansor, Norma Alias, Kamal Zulkifle and Mohammad Khatim Hasan, “A Distributed Memory Parallel Fourth-Order IADEMF Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 10(9), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100979
@article{Mansor2019,
title = {A Distributed Memory Parallel Fourth-Order IADEMF Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100979},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100979},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {9},
author = {Noreliza Abu Mansor and Norma Alias and Kamal Zulkifle and Mohammad Khatim Hasan}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.