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Faculty of Mathematics, Physics & Computer Science

Scientific Computing, Master of Science (M.Sc.)

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Practical Course on Parallel Numerical Methods

The Practical Course on Parallel Numerical Methods is held every year at the end of the winter term by the Chair of Parallel and Distributed Systems in cooperation with the Chair of Scientific Computing.

Supervisor: Markus Scherg (Parallel and Distributed Systems), Thomas Rau (Scientific Computing)

Next course: 30.03.20 - 09.04.20  Cancelled ​(Information for an alternative date will follow)

Location: AI 1.37 (Applied Computer Sciences)


In this practical course, students implement manageable numerical problems (such as PCG method, finite element discretization of 2d Laplacian, etc.) on parallel computers using the programming language C/C++ and standard software libraries (LAPACK/BLAS, OpenMP, OpenMPI). The resulting parallel efficiency is observed depending on the chosen implementation (naive or advanced such as Schwarz methods).

Recommended Prerequisities

  • A1: Numerical Methods for Differential Equations
  • C1.3: Parallel and Distributed Systems I
  • D1.1: Efficient Treatment of Non-local Operators


Implemetation and presentation of approaches; active participation and discussion


1. Course on Parallel Numerical Methods (WS 19/20): 30.03.20 - 09.04.20 at AI 1.37

Webmaster: Maximilian Bauer

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