Difference between revisions of "Scientific Computing II - Summer 13"

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| June 4 || [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss13/conjugate.pdf CG and Preconditioning (cont.)]
| June 4 || [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss13/conjugate.pdf CG and Preconditioning (cont.)]
|| June 10 || <!-- [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/04_steepest_descent_cg_tutorial.pdf Steepest-Descent/CG] <br> [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/04_tutorial_krylov.pdf Slides] --> || <!-- [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/frame-sd.tar.gz SD/CG] [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/SOLUTION_SD.tar.gz Solution-SD] -->
|| June 10 || [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss13/uebungen/blatt6angabe.pdf Sheet6], [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss13/uebungen/blatt6_solution.pdf Solution]<!-- [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/04_steepest_descent_cg_tutorial.pdf Steepest-Descent/CG] <br> [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/04_tutorial_krylov.pdf Slides] --> || <!-- [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/frame-sd.tar.gz SD/CG] [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_04/SOLUTION_SD.tar.gz Solution-SD] -->

Revision as of 13:01, 4 June 2013

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
Semesterwochenstunden / ECTS Credits
2V + 2Ü / 5 Credits
Scientific Computing II


  • 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


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


  • 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 https://matlab.rbg.tum.de/