Daniel Arndt - Interdisciplinary Center for Scientific Computing
Daniel Arndt


Dr. Daniel Arndt
Interdisciplinary Center for Scientific Computing (IWR)
Im Neuenheimer Feld 205
Room 1.412
69120 Heidelberg
Tel: +49 (0)6221-54 14538
E-Mail http://www.mathsim.eu/~darndt

Blockkurs deal.II

Lecturer Daniel Arndt
Class data: LSF
Date 10.10.2016-14.10.2016 09:00-16:00
Room Mathematikon (INF 205), PC-Pool SW 1


deal.II is a free, open source library to solve partial differential equations using the finite element method. The aim of this course is to provide an introduction into this framework. After this course, students should be able to implement suitably easy problems in deal.II.

The course will take place in the PC-Pool SW 1 with a preinstalled deal.II version. Since you will need your own installation for your final project, it is recommended to install deal.II on your own notebook. For using amandus, you will need to use a developer version. Instructions for installing can be found here. Files used in the course can be found here.

Target group

Students of mathematics (BSc and MSc) as well as students of scientific computing (MSc).
The seminar is in particular recommended for those students simultaneously taking the seminar Seminar Numerical Methods for Parabolic Problems and Eigenvalue Problems. It is possible to use the implementation for a talk in this seminar as final project.

Prior Knowledge

Basic knowledge of FEM and C++ is required.


The number of participants is limited to 25 students. Please register via e-mail containing subject of study, semester and academic degree. Preferrably, also state subjects of interest for the course and a problem you want to solve using deal.II.

For the successful completion of the final project (project summary, short presentation) 6 CP are awarded.


We will loosely follow the outline
  1. Short introduction to FEM and deal.II
  2. Creating and refining meshes. Setting up finite element spaces.
  3. A first Poisson solver
  4. A multilevel Poisson solver with discontinuous Galerkin methods
  5. Amandus
  6. Mixed finite elements
  7. Time-dependent problems
  8. Eigenvalue problems
  9. Exploring error estimation and adaptive refinement
  10. Parallelization (MPI)

Project Summary

  • The project summary has to be written using doxygen or LaTeX.
  • Code has to be suitably commented.