Scientific Computing II
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
Module version of WS 2017/8 (current)
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
|available module versions|
|WS 2017/8||SS 2012||WS 2011/2|
IN2141 is a semester module in English language at Master’s level which is offered in summer semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
|Total workload||Contact hours||Credits (ECTS)|
|150 h||60 h||5 CP|
Content, Learning Outcome and Preconditions
- Iterative solution methods for large, sparse linear systems (relaxation methods, geometric and algebraic multigrid methods, Krylov-subspace methods, preconditioning techniques); intuitive introduction, mathematical performance analysis and sample computations
- Molecular dynamics simulation as a case study for the particle-based simulation approaches in scientific computing (overview; modelling of molecular dynamics; discretization approaches; efficient implementation of all-to-all interaction; techniques for parallelization)
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VI||4||Scientific Computing II (IN2141)||Bader, M. Gratl, F. Krenz, L.||
Tue, 10:00–12:00, MI HS2
Fri, 14:00–16:00, MI HS2
Learning and Teaching Methods
- J.R. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain. Edition 1.25. 1994.
- W. Hackbusch. Iterative Solution of Large Sparse Systems of Equations. Springer, 1993.
- Y. Saad. Iterative Methods for sparse linear systems, SIAM 2003.
- M. Griebel, S. Knapek, G. Zumbusch, and A. Caglar. Numerical Simulation in Molecular Dynamics. Springer, 2007.
- M. P. Allen and D. J. Tildesley. Computer Simulation of Liquids. Oxford University Press, 2003.
- D. Frenkel and B. Smith. Understanding Molecular Simulation from Algorithms to ASpplications. Academic Press (2nd ed.), 2002.
- R. J. Sadus. Molecular Simulation of Fluids; Theory, Algorithms and Object-Orientation. Elsevier, 1999.
- D. Rapaport. The art of molecular dynamics simulation. Camebridge University Press, 1995.
Description of exams and course work
The exam may be repeated at the end of the semester.
Current exam dates
Currently TUMonline lists the following exam dates. In addition to the general information above please refer to the current information given during the course.
|Scientific Computing II|
|Thu, 2022-10-06, 11:15 till 13:00||1450
||till 2022-09-26 (cancelation of registration till 2022-09-29)|