Introduction to Scientific Computing II - Summer 11

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Term
Summer 11
Lecturer
Dr. rer. nat. habil. Miriam Mehl, Univ.-Prof. Dr. Hans-Joachim Bungartz
Time and Place
Tuesday 8:15-10:00, lecture room MI 02.07.023
First Lecture: May 3
Audience
Computational Science and Engineering, 2nd semester (Module IN2141)
Tutorials
Wolfgang Eckhardt
Monday 9:00-9:45, lecture room MI 02.07.023,
First Tutorial: May 9
Exam
written exam
Semesterwochenstunden / ECTS Credits
2V + 1Ü / 4 Credits
TUMonline
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Announcements

Contents

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

Annotated slides are available from the TeleTeachingTool Lecture Archive

lecture material tutorial exercise matlab
May 03 Slides May 09 Towards Multigrid
Matlab
Slides
Code Tutorial
Two-Grid-Solver
May 10 Slides
Notes
Full Weighting
May 16 Anisotropic Multigrid
Slides
interpolate_4h.m
restrict_4h.m
restrict_fw.m
Solution Ex. 1
May 17 Slides
Notes
Fourier Analysis Two Grid Method
May 23 Steepest Descent / CG Anisotropic MG
Solution



Main

May 24 Slides
Notes
May 30 Parallel MG / SD / CG
May 31 Slides
Notes
June 6
June 7 Slides
Notes
June 13 no tutorial!!
June 14 no lecture! June 20

Exam

Literature

  • 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.