Scientific Computing II - Summer 14
- Term
- Summer 2014
- Lecturer
- Prof. Dr. Michael Bader
- Time and Place
- Tuesday 10-12, lecture room MI 02.07.023
First Lecture: Apr 8 - Audience
- Computational Science and Engineering, 2nd semester
others: see module description - Tutorials
- Kaveh Rahnema (time and place t.b.a.)
Monday 10-12, lecture room MI 02.07.023,
First Tutorial: April 14 - Exam
- written exam
- Semesterwochenstunden / ECTS Credits
- 2V + 2Ü / 5 Credits
- TUMonline
- Scientific Computing II
Announcements
- on June 16, we will restart with a lecture (which replaces the usual tutorial)
Contents
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 students in computer science, mathematics, or some field of science or engineering who already have a certain background in the numerical treatment of (partial) differential equations.
Lecture Notes and Material
will be made available throughout the lecture ...
| lecture | material | tutorial | exercise | matlab |
| Apr 8 | Introduction, Relaxation Methods | Apr 14 | sheet1 , solution1 | |
| Apr 15 | Multigrid Methods (Part I), Animations | Apr 21 | - (Easter holiday) | |
| Apr 28 (Mon) | Multigrid Methods (Part II) | Apr 29 (Tue) | sheet2 , solution2 | smoothers.m |
| May 05 (Mon) | Multigrid Methods (Part II cont., Part III) | May 12 | sheet3 ,solution3 | code_exercise3 |
| May 13 | Multigrid Methods (Part III) | May 19 | sheet4, solution4 | smooth.m, code_exercise4 |
| May 20 | Steepest Descent and Conjugate Gradient Methods (Maple worksheet quadratic_forms.mws, also as PDF) |
May 26 | sheet5, solution5 | |
| May 27 | CG and Preconditioning (Maple worksheet conjugate_gradient.mws, also as PDF) |
Jun 2 | sheet6 | |
| Jun 3 | CG and Preconditioning (cont) | Jun 9&10 | lecture and tutorial cancelled (holidays) |
Literature
- William L. Briggs, Van Emden Henson, Steve F. McCormick. A Multigrid Tutorial. Second Edition, SIAM, 2000 (available as eBook in the TUM library)
- Ulrich Trottenberg, Cornelis Oosterlee, Anton Schüller. Multigrid. Elsevier, 2001 (available as eBook in the TUM library)
- J.R. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain (download as PDF). 1994.
- V. Eijkhout: Introduction to High-Performance Scientific Computing (textbook, available as PDF on the website)
- M. Griebel, S. Knapek, G. Zumbusch, and A. Caglar. Numerical simulation in molecular dynamics. Springer, 2007 (available as eBook in the TUM library)
- 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 Applications. 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/