Analysis of the interaction of electromagnetic signals with thin-wires structures. multiprocessing issues for an iterative method

Authors:
E. M. Garzón;S. Tabik;A. R. Bretones;I. García
Affiliations:
Dept. Computer Architecture and Electronics, University of Almería, Almería, Spain;Dept. Computer Architecture and Electronics, University of Almería, Almería, Spain;Dept. Electromagnetism and Physics of the Matter, Faculty of Sciences, University of Granada, Granada, Spain;Dept. Computer Architecture and Electronics, University of Almería, Almería, Spain
Venue:
VECPAR'04 Proceedings of the 6th international conference on High Performance Computing for Computational Science
Year:
2004

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Abstract

In this paper we analyse the computational aspects of a numerical method for solving the Electric Field Integral Equation (EFIE) for the analysis of the interaction of electromagnetic signals with thin-wires structures. Our interest concerns with the design of an efficient parallel implementation of this numerical method which helps physicist to solve the Electric Field Integral Equation for very complex and large thin-wires structures. The development of this parallel implementation has been carried out on distributed memory multiprocessors, with the use of the parallel programming library MPI and routines of PETSc (Portable, Extensible Toolkit for Scientific Computation). These routines can solve sparse linear systems in parallel. Appropriate data partitions have been designed in order to optimize the performance of the parallel implementation. A parameter named relative efficiency has been defined to compare two parallel executions with different number of processors. This parameter allows us to better describe the superlinear performance behavior of our parallel implementation. Evaluation of the parallel implementation is given in terms of the values of the speep-up and the relative efficiency. Moreover, a discussion about the requirements of memory versus the number of processors is included.It will be shown that memory hierarchy management plays a relevant role in the performance of this parallel implementation.