Introduction to Scientific Computing II - Summer 12

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Summer 12
Prof. Dr. Michael Bader
Time and Place
Tuesday 8:30-10:00, lecture room MI 02.07.023
First Lecture: April 17
Computational Science and Engineering, 2nd semester (Module IN2141)
Wolfgang Eckhardt
lecture room MI 02.07.023, time:
Monday 9:00-9:45,
First Tutorial: April 23
written exam
Semesterwochenstunden / ECTS Credits
2V + 1Ü / 4 Credits
Scientific Computing II




This course provides a deeper knowledge in two important fields of scientific computing:

  • solution of large sparse systems of linear equations:
    • Gaussian elemination
    • relaxation methods
    • multigrid methods
    • steepest descent
    • conjugate gradient methods
  • molecular dynamics simulations
    • the physical model
    • the mathematical model
    • approximations and discretization
    • implementational aspects
    • parallelisation
    • examples of nanofluidic simulations

The course is conceived for computer scientists, mathematicians, engineers, or natural scientists with already a background in the numerical treatment of (partial) differential equations.

Lecture Notes and Material

lecture material tutorial exercise matlab
Apr 17 Introduction, Relaxation Methods Apr 23 Slides Matlab Code
Apr 24 Multigrid Methods, Animations Apr 30 Iterative Solvers Homework Sheet Matlab Code
Mai 1 (holiday - no lecture)

Further Material

Annotated slides for the lecture in summer 2010 /(given by Dr. Tobias Weinzierl) are available from the TeleTeachingTool Lecture Archive

Matlab (together with installation instructions) is available from


  • 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.
  • M. Griebel, S. Knapek, G. Zumbusch, and A. Caglar. Numerische Simulation in der Molekulardynamik. Springer, 2004.
  • 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.