Overview
ABSTRACT
Within the automobile industry, the medical sector or in astrophysics the complex problems of structure calculations and shape recognition are currently solved on parallel calculators composed of hundreds of calculation nodes. The way in which they function requires the use of domain decomposition methods. The first models regarding such methods were defined by H.A. Schwarz. The main principle consists in the breaking down of a large scale problem into a series of smaller problems which thus become easier to solve. Since their creation, these approaches have evolved and variations have been added to the basic models thus leading to various convergence qualities.
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Read the articleAUTHORS
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Martin J. GANDER: Mathematics teacher - Mathematics Section, University of Geneva
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Laurence HALPERN: Mathematics teacher - Analysis, Geometry and Applications Laboratory, Université Paris 13
INTRODUCTION
All engineering problems today are solved in parallel on computers with hundreds or even thousands of compute nodes. This article describes domain decomposition methods that can be applied to these new tools. Emile Picard teaches us in that to understand a theory, it's good to have a model problem in mind.
The approximation methods we use are theoretically applicable to any equation, but they only become really interesting for studying the properties of functions defined by differential equations if we go beyond generalities and consider certain classes of equations.
Throughout this presentation, we'll choose a common thread: the heat equation.
representing the variations in time and space of the temperature of a body filling the domain Ω, subjected to a heat source f (which will be called the second member), with a given initial temperature throughout the domain, and boundary conditions on the edge of the domain ∂Ω, e.g. Dirichlet (the temperature is fixed), i.e. u = g. ∂
t
u is the time derivative of u, Δ is the Laplace operator, Δu = ∂
11
u + ∂
22
u + ∂
33
u. To calculate an approximate solution to this equation on a computer, we can start with a semi-discretization in time. The simplest scheme is the implicit Euler scheme (see
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KEYWORDS
| | Domain Decomposition | Schwarz Methods | Schur's Methods | Waveform Relaxation | Parareal Algorithm
Domain decomposition methods
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