Scientific computing

Basic training in numerical methods and programming (level of LFSAB1104).

• Numerical software in C++ and Python
• Parallel computing
• Numerical methods for partial differential equations

Contribution of the course to the program objectives (Nr) :

• AA1.1, AA1.2, AA1.3
• AA2.2, AA2.3, AA2.4
• AA3.2
• AA6.1, AA6.3

After successful completion of this course, the student will be able to:

• Write, modify and use numerical software in C++ and Python;
• Write, modify and use scientific software for partial differential equations;
• Employ parallel programming techniques

Transversal learning outcomes :

• Use a reference book in English;
• Use programming languages for scientific computing;
• Release software along with suitable user documentation.

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.

• Homeworks, exercises, or laboratory work during the course semester
• Exam

Clarifications are provided in the course outline (plan de cours) available on Moodle.

• Interactive lectures
• Homework assignments, exercises, or laboratory work under the supervision of the teaching assistants

• Programming concepts in C++ and Python
• Numerical software engineering in C++ and Python
• Analysis of partial differential equations
• Finite-difference methods for partial differential equations
• Introduction to parallel computing using MPI
• Other topics related to the course themes.

• Reference books
• Complementary documents posted on Moodle

Precisions are given in the course outline (plan de cours) available on Moodle.

The organisation details are given every year in the course plan.