Scientific Computing II - Summer 13

Term

Summer 13

Lecturer

Prof. Dr. Michael Bader

Time and Place

Tuesday 10-12, lecture room MI 02.07.023
First Lecture: Apr 16

Audience

Computational Science and Engineering, 2nd semester

Tutorials

Wolfgang Eckhardt Philipp Neumann
Monday 10-12, lecture room MI 02.07.023,
First Tutorial: April 22

Exam

written exam

Semesterwochenstunden / ECTS Credits

2V + 2Ü / 5 Credits

TUMonline

Scientific Computing II

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Announcements

• lecture on Tuesday, July 2, will move to Monday, July 1, 12.00-13.30 (room MI 02.07.023): for organizational reasons, the lectures Numerical Programming II and Scientific Computing will be swapped on these two days
• 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)

Exam

• written exam

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 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, Code_Ex5, Code_Ex6, Solution_Ex5, Solution_Ex6
June 11	Molecular Dynamics (Intro) (Maple worksheet twobody.mws, also as PDF	June 17	Sheet7, Solution, code_exercise7.tar
June 18	Molecular Dynamics, Pt. 1	June 24	Sheet8, Solution, code_exercise8.tar
June 25	Time Integration Maple worksheet circles_ode.mws, also as PDF)	July 1

Literature

• 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/