Scientific Computing II - Summer 13
- 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
- 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
|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.
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/