Abstract: Any electromagnetic device is the house of two or more physical fields that interact by a number of parameters as the material properties, the field sources etc. In other words we have not separate problems for engineers from different science branches although for economic reasons in terms of computer resources, each physical field is considered as though it was separate field and generates a problem which is solved independently. The subsystems and numerical solutions are finally coupled together in such way that interactions are satisfied with an "acceptable" degree of accuracy. This is a natural approach for the analysis of large or complex structures but the accuracy of the analysis is not good.
The technique of dividing a large physical system into a system of components is very old and is still used extensively although the reasons of this approach are not valid nowadays. We have an increased computing power with advanced computer architectures so that it is an antisocial fact to ignore this real computing power.
In our lecture we intend to review the state-of-the-art of iterative methods for solving large sparse systems such as arising in coupled engineering problems. The solution of practical problems of mathematical physics ultimately relies on solving a system of partial derivative equations and this is only achieved by iterative numerical methods. Iterative solution methods proceed by adding successive corrections to some arbitrary initial approximation, but unfortunately these methods are very sensitive to specific features of the system to be solved. A procedure call preconditioning is possible but is not always used.
We limit our presentation to a large class of systems defined by elliptic-parabolic mathematical models that represents the basis of the electromagnetic-thermal problems. The numerical models are obtained by the finite differences and finite element methods. The motivation is simple: for parabolic problems we use an explicit scheme for temporal discretization, and for elliptic problem we use the finite element method. As target example we use an electromagnetic-thermal coupled problem from electrical engineering.
In the algorithmic skeletons for this class of problems we are guided by the implementation of the algorithms on the parallel computers with emphasis on parallel computers (MIMD architectures).

Brief Biography of the Speaker:
The speaker is an Assoc. Professor at the Computer Engineering and Communications Department, Faculty of Automatics, Computers and Electronics, University of Craiova, Romania.
He has a BSc and MSc in Automatics from the University of Craiova, Romania. He has a Ph.D. in Automatics from the University of Ploiesti, Romania. Also, he has a BSc and MSc in Mathematics from the Natural Sciences Faculty, University of Craiova, Romania.
He was director of the research projects supported by international grants at University of Houston (USA)- 6 months (Fulbright Grant), at the University of Coimbra, Portugal – 9 months (NATO grant), at the Polytechnics of Milano, Italy- 4 months (a CNR-NATO grant). In 2004 he was invited at the Mathematics Department, University of Trento, Italy, for 2 months.
Ion Carstea published 10 books in the area of programming languages advanced computers and CAD of the electromagnetic devices. He is the co-author of the book FINITE ELEMENTS in WSEAS Press, 2007.
He is the author of more than 160 papers in revues, scientific journals and international conference proceedings. He is a reviewer for several WSEAS International Conferences and was a member in many international scientific committees. In the year 2007, he was a Plenary speaker and chair at the WSEAS Conferences from Arcachon (France) and Venice (Italy). In 2008 he was Plenary speaker to two WSEAS Conferences from Bucharest (June 2008, November 2008).
His research interests include parallel algorithms for numerical simulation of the distributed-parameter systems, software products for coupled and inverse problems in engineering, domain decomposition method in the context of the finite element method.