Scientific Computing II - Summer 13

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Summer 13
Prof. Dr. Michael Bader
Time and Place
Tuesday 10-12, lecture room MI 02.07.023
First Lecture: Apr 16
Computational Science and Engineering, 2nd semester
Wolfgang Eckhardt Philipp Neumann
Monday 10-12, lecture room MI 02.07.023,
First Tutorial: April 22
written exam: July 24, 8.30-10.00 in lecture hall Interim 2
Semesterwochenstunden / ECTS Credits
2V + 2Ü / 5 Credits
Scientific Computing II


  • lecture on Tuesday, July 2, will move to Monday, July 1, 12.00-13.30 (room MI 02.07.023): for organizational reasons, the lectures Numerical Programming II and Scientific Computing will be swapped on these two days
  • due to the student assembly, the lecture on Tuesday, May 14, is skipped
  • due to a short holiday (Whit Monday/Pentecost), lecture and tutorial on May 20/21 will be skipped
  • on Mon 27, we will restart with a lecture (which replaces the usual tutorial)


  • written exam
  • Date: Wed, 24 July 2013
  • Time: 8:30 - 10:00
    Please make sure to be in the lecture hall by 8:15, as the exam will start precisely at 8.30.
  • Place: Interim 2 (one of the lecture halls in the black buildig in front of MI)
  • Duration: 90 min.
  • auxiliary material allowed:
    • one hand-written sheet of paper (Din A4), written on both sides
    • You are not allowed to use any other tools / devices (e.g. electronic dictionaries)

Please make sure that you are registered for the exam via TUMOnline!

Old exams are available on the websites of the last years (note that this year, the extent of the lecture was extended!):


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

  • iterative solution of large sparse systems of linear equations:
    • 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 16 Introduction, Relaxation Methods Apr 22 Sheet1, Solution
Apr 23 Multigrid Methods, Animations Apr 29 Sheet2, Solution, smoothers.m
Apr 30 Multigrid Methods (Part II) May 06 Sheet3, Solution, code_exercise3.tar
May 07 Multigrid Methods (Part III) May 13 Sheet4, smooth.m, Solution, code_exercise4.tar
Mai 14 (student assembly - no lecture) May 20 (holiday - no lecture)
Mai 21 (holiday - no lecture) May 27 Steepest Descent and Conjugate Gradient Methods
(Maple worksheet quadratic_forms.mws, also as PDF)
May 28 CG and Preconditioning
(Maple worksheet conjugate_gradient.mws, also as PDF)
June 3 Sheet5, Solution
June 4 CG and Preconditioning (cont.) June 10 Sheet6, Solution, Code_Ex5, Code_Ex6, Solution_Ex5, Solution_Ex6
June 11 Molecular Dynamics (Intro)
(Maple worksheet twobody.mws, also as PDF
June 17 Sheet7, Solution, code_exercise7.tar
June 18 Molecular Dynamics, Pt. 1 June 24 Sheet8, Solution, code_exercise8.tar
June 25 Time Integration
Maple worksheet circles_ode.mws, also as PDF)
July 1 Sheet9, Solution, code_exercise9.tar
July 1 short-range potentials and (parallel) implementation July 8 Sheet10, Solution July 8 t.b.d. July 15 Sheet11, Solution


  • William L. Briggs, Van Emden Henson, Steve F. McCormick. A Multigrid Tutorial. Second Edition. SIAM. 2000.
  • Ulrich Trottenberg, Cornelis Oosterlee, Anton Schüller. Multigrid. Elsevier, 2001.
  • J.R. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain (download as PDF). 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.

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