|Term:||Winter Term 2020/21|
|Time and location:||Di 14-16; Thu 14-16|
|Exam:||to be announced|
eLearning Concept of this Lecture and Exercises
I planned to give this lecture in a hybrid format, but due to the recent decisions to fight the pandemic, no teaching in presence will be possible, at least in November.
So this course will be carried out as follows: https://heiconf.uni-heidelberg.de/ku2e-6rdd-qyq2-tymc
- Lecture will be given in the heiCONF virtual room Parsolve Lecture Room on Tuesday 14:15-15:45 and Thursday 14:15-15:45 (no key necessary)
- Tablet presentation and voice will be recorded and put online in Mampf, so you can follow the lecture also offline
- Material, exercise sheets and forum discussion is done via a moodle page (inscription see below)
- Exercises will take place on Thursday 9:15-10:45 in the same heiCONF room as the lecture: Parsolve Lecture Room
- I hope that most of you will participate in the life events, where we can interact and discuss
Contents of the Lecture
This lecture gives an introduction to domain decomposition and multigrid methods. It covers the theory based on subspace decomposition and is structured as follows:
- Parallelization of classical linear iterative methods
- Overlapping domain decomposition methods, Schwarz methods
- Multigrid methods
- Non-overlapping domain decomposition methods
In order to see the detailed contents of the lecture you can have a look into the lecture notes.
Go to the (moodle page for this course).
The key for self inscription to the moodle course is: Parsolve2020
The exercise will take place virtual in the heiCONF room Parsolve Lecture Room every Thursday 9:15-10:45. The first exercise will take place on November 12th.
Exercises will be published here and probably in MaMpf or moodle.
- Exercise 00
- Exercise 01
- Exercise 02
- Exercise 03
- Exercise 04
- Exercise 05
- Exercise 06
- Exercise 07
- Exercise 08
If you have any questions you can write an email to email@example.com.
Dune Installation Script
The installation script mentioned on the exercise sheet 0 can be found here.