Difference between revisions of "Introduction to Scientific Computing II - Summer 12"

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| July 3 || [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/moldyn_01.pdf Molecular Dynamics (Modelling)]<br>[http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/moldyn_02.pdf Time Integration] || July 9
| July 3 || [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/moldyn_01.pdf Molecular Dynamics (Modelling)]<br>[http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/moldyn_02.pdf Time Integration] || July 9
|| ||   
|| [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_C/C_discretisation_tutorial.pdf MD Discretisation] <BR> [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss12/tutorial_C/C_discretisation_tutorial_solution.pdf solution]||   

Revision as of 07:28, 9 July 2012

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)

May 7

Solution Homework Exercise Code Tutorial
May 8 Multigrid Methods (cont.) May 14 slides Multigrid-Solver 2Grid-Solver
May 15 Multigrid Methods (cont.),
May 21 Multigrid Multigrid-Solver



May 22 Slides
Two-grid analysis
May 28 - (holiday) -
May 29 - (holiday) June 4 - -
June 5 Steepest Descent and Conjugate Gradient Methods
(Maple worksheet quadratic.mws, also as PDF)
June 11 Steepest-Descent/CG
SD/CG Solution-SD
June 12,19 Preconditioned Conjugate Gradient Methods
(Maple worksheet conjugate_gradient.mws, also as PDF)
June 18 PCG PCG-Frame Solution
June 19 Molecular Dynamics (Intro and Modelling) June 25 MD Introduction
June 26 Molecular Dynamics (Intro and Modelling)
(Maple worksheet twobody.mws, also as PDF;
Maple worksheet circles_ode.mws, also as PDF)
July 2 MD Modelling
July 3 Molecular Dynamics (Modelling)
Time Integration
July 9 MD Discretisation

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/


  • 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 (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.