Scientific Computing II

Module IN2141

This Module is offered by TUM Department of Informatics.

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 SS 2012 (current)

There are historic module descriptions of this module. A module description is valid until replaced by a newer one.

available module versions
SS 2012WS 2011/2

Basic Information

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 workloadContact hoursCredits (ECTS)
150 h 60 h 5 CP

Content, Learning Outcome and Preconditions


The lecture gives deeper insight into two important topics of scientific computing: - 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)

Learning Outcome

At the end of the module, students are able to remember and identify the main classes of iterative methods to solve large, sparse linear systems. The participants can evaluate the range of application of such methods in standard scenarios, they are familiar with their basic performance features, and they can apply and implement them. They are familiar with the typical steps of the simulation pipeline from modeling over discretization and numerics to implementation and visualization. For the scenario Molecular Dynamics, they have detailed knowledge of these steps and are able to design and realise suitable simulation software.


Students should have basic knowledge in differential calculus and linear algebra. Knowlegde in numerical programming and scientic computing is recommended (modules IN2005 and IN0019, e.g.).

Courses, Learning and Teaching Methods and Literature

Courses and Schedule

VU 4 Scientific Computing II (IN2141) Montag, 14:00–16:00
Dienstag, 10:00–12:00

Learning and Teaching Methods

This module comprises lectures and accompanying tutorials. The contents of the lectures will be taught by talks and presentations. Students will be encouraged to study literature and to get involved with the topics in depth. In the tutorials, concrete problems will be solved - partially in teamwork - and selected examples will be discussed.


Slides, whiteboard, exercise sheets


- William L. Briggs, Van Emden Henson, Steve F. McCormick. A Multigrid Tutorial. Second Edition. SIAM. 2000. - 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.

Module Exam

Description of exams and course work

Type of Assessment: exam In the exam students should prove to be able to identify a given problem and find solutions within limited time. The examination will completely cover the content of the lectures. The answers will require own formulations. In addition, questions requiring short calculations may be posed. Exam questions test the participants' capability to remember and identify the main classes of iterative methods to solve large, sparse linear systems and to explain their basic performance features. The students demonstrate that they are familiar with the typical steps of the simulation pipeline from modelling over discretisation and numerics to implementation and visualization.

Exam Repetition

There is a possibility to take the exam 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
Mo, 10.10.2016, 8:00 bis 9:45 102
bis 19.9.2016 (Abmeldung bis 3.10.2016)

Condensed Matter

When atoms interact things can get interesting. Fundamental research on the underlying properties of materials and nanostructures and exploration of the potential they provide for applications.

Nuclei, Particles, Astrophysics

A journey of discovery to understanding our world at the subatomic scale, from the nuclei inside atoms down to the most elementary building blocks of matter. Are you ready for the adventure?


Biological systems, from proteins to living cells and organisms, obey physical principles. Our research groups in biophysics shape one of Germany's largest scientific clusters in this area.