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Network-on-chip multicore architectures with a large number of processing elements are becoming a reality with the recent developments in technology. In these modern systems the processing elements are interconnected with regular network-on-chip (NoC) topologies such as meshes and trees. In this paper we propose a parallel Gauss-Seidel (GS) iterative algorithm for solving large systems of linear equations on a torus NoC architecture. The proposed parallel algorithm is O(Nn²/k²) time complexity for solving a system with matrix of order n on a k × k torus NoC architecture with N iterations assuming n and N are large compared to k (i.e. for large linear systems that require a large number of iterations). We show that under these conditions the proposed parallel GS algorithm has near optimal speedup.

In this paper, a new iterative method, for solving sparse nonsymmetrical systems of linear equations is proposed based on the Simultaneous Elimination and Back-Substitution Method (SEBSM), and the method is applied to solve systems resulted in engineering problems solved using Finite Element Method (FEM). First, SEBSM is introduced for solving general linear systems using the direct method. And, then an iterative method based on SEBSM is presented. In the method, the coefficient matrix $A$ is split into lower, diagonally banded and upper matrices. The iterative convergence can be controlled by selecting a suitable bandwidth of the diagonally banded matrix. And the size of the working array needing to be stored in iteration is as small as the bandwidth of the diagonally banded matrix. Finally, an accelerating strategy for this iterative method is proposed by introducing a relaxation factor, which can speed up the convergence effectively if an optimal relaxation factor is chosen. Two numerical examples are given to demonstrate the behavior of the proposed method.

Load flow (LF) analysis is one of the most important aspects in power system studies. It is the most significant and necessary way to investigate the problems in power system operation and planning. The LF problem comprises a set of nonlinear algebraic equations that must be solved mathematically through iterations. The solution convergence is the most important criteria that is largely affected by the size of power system, which continues to increase in the current modern power system field. Thus, there is no guarantee that the iterative approaches will converge to a valid solution for problems with such large dimensions. This paper develops generalized, effective and simple mathematical models for the solution of the LF problem. The problem is first solved by Gauss–Seidel (GS) method in order to generate the training data. Eureqa software is then adopted for the purpose of data training and mathematical models generation. The models relate bus voltage magnitudes and angles as output parameters with the load active and reactive power values as input parameters. To study the validity of the proposed approach, the mathematical models have been developed for two benchmark test systems; IEEE 5-bus test system and 9-bus test system developed by Western Systems Coordinating Council (WSCC). When compared with the outputs resulting from GS technique, the results have shown efficient and accurate capability of the generated models for evaluating bus voltages magnitudes and angles as well as generated reactive power. The models have also been compared with other published research. The results have shown efficient performance of the developed models.