Schnelle Löser für Partielle Differentialgleichungen

The workshop Schnelle Löser für partielle Differentialgleichungen, organised by Randolph E. Bank (La Jolla), Wolfgang Hackbusch (Leipzig), and Gabriel Wittum (Frankfurt am Main), was held May 22nd–May 28th, 2011. This meeting was well attended by 54 participants with broad geographic representation from 7 countries and 3 continents. This workshop was a nice blend of researchers with various backgrounds

A study on block flexible iterative solvers with applications to Earth imaging problem in geophysics

Les travaux de ce doctorat concernent le développement de méthodes itératives pour la résolution de systèmes linéaires creux de grande taille comportant de nombreux seconds membres. L’application visée est la résolution d’un problème inverse en géophysique visant à reconstruire la vitesse de propagation des ondes dans le sous-sol terrestre. Lorsque de nombreuses sources émettrices sont utilisées, ce problème inverse nécessite la résolution de systèmes linéaires complexes non symétriques non hermitiens comportant des milliers de seconds membres. Dans le cas tridimensionnel ces systèmes linéaires sont reconnus comme difficiles à résoudre plus particulièrement lorsque des fréquences élevées sont considérées. Le principal objectif de cette thèse est donc d’étendre les développements existants concernant les méthodes de Krylov par bloc. Nous étudions plus particulièrement les techniques de déflation dans le cas multiples seconds membres et recyclage de sous-espace dans le cas simple second membre. Des gains substantiels sont obtenus en terme de temps de calcul par rapport aux méthodes existantes sur des applications réalistes dans un environnement parallèle distribué. ABSTRACT : This PhD thesis concerns the development of flexible Krylov subspace iterative solvers for the solution of large sparse linear systems of equations with multiple right-hand sides. Our target application is the solution of the acoustic full waveform inversion problem in geophysics associated with the phenomena of wave propagation through an heterogeneous model simulating the subsurface of Earth. When multiple wave sources are being used, this problem gives raise to large sparse complex non-Hermitian and nonsymmetric linear systems with thousands of right-hand sides. Specially in the three-dimensional case and at high frequencies, this problem is known to be difficult. The purpose of this thesis is to develop a flexible block Krylov iterative method which extends and improves techniques already available in the current literature to the multiple right-hand sides scenario. We exploit the relations between each right-hand side to accelerate the convergence of the overall iterative method. We study both block deflation and single right-hand side subspace recycling techniques obtaining substantial gains in terms of computational time when compared to other strategies published in the literature, on realistic applications performed in a parallel environment

Adaptive Coarse Spaces for FETI-DP and BDDC Methods

Iterative substructuring methods are well suited for the parallel iterative solution of elliptic partial differential equations. These methods are based on subdividing the computational domain into smaller nonoverlapping subdomains and solving smaller problems on these subdomains. The solutions are then joined to a global solution in an iterative process. In case of a scalar diffusion equation or the equations of linear elasticity with a diffusion coefficient or Young modulus, respectively, constant on each subdomain, the numerical scalability of iterative substructuring methods can be proven. However, the convergence rate deteriorates significantly if the coefficient in the underlying partial differential equation (PDE) has a high contrast across and along the interface of the substructures. Even sophisticated scalings often do not lead to a good convergence rate. One possibility to enhance the convergence rate is to choose appropriate primal constraints. In the present work three different adaptive approaches to compute suitable primal constraints are discussed. First, we discuss an adaptive approach introduced by Dohrmann and Pechstein that draws on the operator P_D which is an important ingredient in the analysis of iterative substructuring methods like the dual-primal Finite Element Tearing and Interconnecting (FETI-DP) method and the closely related Balancing Domain Decomposition by Constraints (BDDC) method. We will also discuss variations of the method by Dohrmann and Pechstein introduced by Klawonn, Radtke, and Rheinbach. Secondly, we describe an adaptive method introduced by Mandel and Sousedík which is also based on the P_D-operator. Recently, a proof for the condition number bound in this method was provided by Klawonn, Radtke, and Rheinbach. Thirdly, we discuss an adaptive approach introduced by Klawonn, Radtke, and Rheinbach that enforces a Poincaré- or Korn-like inequality and an extension theorem. In all approaches generalized eigenvalue problems are used to compute a coarse space that leads to an upper bound of the condition number which is independent of the jumps in the coefficient and depend on an a priori prescribed tolerance. Proofs and numerical tests for all approaches are given in two dimensions. Finally, all approaches are compared