Iterative methods, particularly over-relaxation methods, are efficiently and frequently used to solve large systems of linear equations, because in the solutions of partial differential equations, these methods are applied to systems which are resulted from different iterative schemes to discrete equations. In this paper we formulate an accelerated over-relaxation (AOR) method with the quarter-sweep iterative scheme applied to the Poisson equation. To benchmark the new method we conducted experiments by comparing it with the previous AOR methods based on full- and half-sweep iterative schemes. The results of the experiments and the estimation of the computational complexity of the methods proved the superiority of the new method.
Kaedah baru pasangan benaman 4(3) tahap-empat berperingkat empat tak tersirat Runge-Kutta-Nyström (RKN) diterbitkan untuk mengamir persamaan pembezaan peringkat dua berbentuk yʺ = f (x, y) dengan penyelesaian bentuk berkala. Dipersembahkan kaedah yang bercirikan serakan berperingkat tinggi serta pekali ralat pangkasan utama yang ‘kecil’. Analisis kestabilan bagi kaedah yang diterbitkan juga diberikan. Perbandingan keputusan berangka antara kaedah yang dihasilkan dengan kaedah RK4(3) dan RKN4(3)D menunjukkan kaedah yang baru ini berkecekapan lebih baik daripada segi penilaian fungsi dan masa pelaksanaan.
Heterogeneous parallel architecture (HPA) are inherently more complicated than their homogeneous counterpart. HPAs allow composition of conventional processors, with specialised processors that target particular types of task. However, this makes mapping and scheduling even more complicated and difficult in parallel applications. Therefore, it is crucial to use a robust modelling approach that can capture all the critical characteristics of the application and facilitate the achieving of optimal mapping. In this study, we perform a concise theoretical analysis as well as a comparison of the existing modelling approaches of parallel applications. The theoretical perspective includes both formal concepts and mathematical definitions based on existing scholarly literature. The important characteristics, success factors and challenges of these modelling approaches have been compared and categorised. The results of the theoretical analysis and comparisons show that the existing modelling approaches still need improvement in parallel application modelling in many aspects such as covered metrics and heterogeneity of processors and networks. Moreover, the results assist us to introduce a new approach, which improves the quality of mapping by taking heterogeneity in action and covering more metrics that help to justify the results in a more accurate way.