12 August 2016
An Introduction to the Theory and Practice of Multigrid Methods
Multigrid (MG) methods provide optimal complexity algorithms for the iterative solution of various classes of discrete elliptic boundary value problems as they arise in the simulation of many (multiphysics) models in engineering and life sciences. MG methods rely on the effective interplay of smoothing on a certain grid and error correction on a coarser grid. The smoothing component has the effect of damping the oscillatory part of the error while the smooth part of the error can then be corrected on a coarser grid. This course will cover the theoretical basis of MG methods but also heuristic algorithms, e.g., algebraic multigrid (AMG), and address important aspects of their application and implementation.
Lecturer: Prof. Johannes Kraus (University of Duisburg-Essen, Germany)
Coordinator: Dr. Immanuel Anjam, and Dr. Sanna Mönkölä (University of Jyväskylä)
Basics in finite element methods and numerical linear algebra. The course is aimed at graduate and advanced undergraduate students and researchers with basic knowledge of numerical linear algebra and numerical partial differential equations.
The Summer School annually offers courses for advanced master’s students, graduate students, and post-docs in the various fields of science and information technology.
The most important aims of the Summer School are to develop post-graduates scientific readiness and to offer students the possibility to study in a modern, scientific environment and to create connections to the international science community. The Summer School offers an excellent pathway to develop international collaboration in post-graduate research.
Passing: Obligatory attendance at lectures, and completing the exercises.
EUR 0: Participating the Summer School is free of charge, but student have to cover the costs of own travel, accommodation and meals at Jyväskylä.
The 26th Jyväskylä Summer School is not able to grant any Summer School students financial support.