# 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:
**July 24, 8.30-10.00**in lecture hall**Interim 2** **Semesterwochenstunden / ECTS Credits**- 2V + 2Ü / 5 Credits
**TUMonline**- Scientific Computing II

## Contents

# 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
- Date:
**Wed, 24 July 2013** - Time: 8:30 - 10:00
**Please make sure to be in the lecture hall by 8:15**, as the exam will start precisely at 8.30. - Place:
**Interim 2**(one of the lecture halls in the black buildig in front of MI) - Duration: 90 min.
- auxiliary material allowed:
- one hand-written sheet of paper (Din A4), written on both sides
- You are not allowed to use any other tools / devices (e.g. electronic dictionaries)

** Please make sure that you are registered for the exam via TUMOnline!**

Old exams are available on the websites of the last years (note that this year, the extent of the lecture was extended!):

http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss11/exam.pdf

http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss10/exam.pdf

http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss08/exam.pdf

# 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

# 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/