Course content

The course is aimed at PhD candidates who want or need to apply High-Performance Computing (HPC) in their research. Course topics are: Mathematical modeling of scientific and engineering problems; computational methods; HPC hardware and software configuration; appropriate and efficient use of computational resources.

Learning outcome

After having passed the course, the candidate will have practical experience in formulating mathematical model for her/his research objectives. The candidate should be able to develop a concept and analysis routine for a numerical simulation. The student should have practical competence in assessing the computational requirements and be able to set up an efficient HPC system to conduct her/his research with.

Learning methods and activities

Lectures on case studies, seminars, programming workshops, self study

Specific conditions

Recommended previous knowledge

Familiar with the physics and governing equations in own research field.Fundamental knowledge in mathematical modeling and analysis, in particular in analysis of differential equations.

Course materials

Selected articles, book and online material from the field of numerical analysis and HPC