Due to the COVID-19 crisis, the information below is subject to change,
in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h + 22.5 h
Q2
Teacher(s)
Absil Pierre-Antoine (coordinator); Meerbergen Karl (compensates Papavasiliou Anthony); Papavasiliou Anthony;
Language
English
Prerequisites
Basic training in numerical methods and programming (level of LFSAB1104).
Main themes
- Numerical software in C++ and Python
- Parallel computing
- Numerical methods for partial differential equations
Aims
At the end of this learning unit, the student is able to : | |
| 1 |
Contribution of the course to the program objectives (Nr) :
|
Content
- Programming concepts in C++ and Python
- Numerical software engineering in C++ and Python
- Analysis of partial differential equations
- Numerical methods for partial differential equations
- Introduction to parallel computing using MPI
- Other topics related to the course themes.
Teaching methods
Due to the COVID-19 crisis, the information in this section is particularly likely to change.
- Interactive lectures
- Homework assignments, exercises, or laboratory work under the supervision of the teaching assistants
Evaluation methods
Due to the COVID-19 crisis, the information in this section is particularly likely to change.
- Homeworks, exercises, or laboratory work during the course semester
- Exam
Other information
The organisation details are given every year in the course outline.
Bibliography
- Ouvrages de référence
- Documents complémentaires disponibles sur Moodle
Faculty or entity
MAP
