Scientific Computing II - Summer 14: Difference between revisions
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| term = Summer 2014 | | term = Summer 2014 | ||
| lecturer = [[Michael Bader|Prof. Dr. Michael Bader]] | | lecturer = [[Michael Bader|Prof. Dr. Michael Bader]] | ||
| timeplace = | | timeplace = Tuesday 10-12, lecture room MI 02.07.023<br/>First Lecture: Apr 8 | ||
| credits = 2V + 2Ü / 5 Credits | | credits = 2V + 2Ü / 5 Credits | ||
| audience = Computational Science and Engineering, 2nd semester <br> others: [https://campus.tum.de/tumonline/wbStpModHB.detailPage?&pKnotenNr=476730 see module description] | | audience = Computational Science and Engineering, 2nd semester <br> others: [https://campus.tum.de/tumonline/wbStpModHB.detailPage?&pKnotenNr=476730 see module description] | ||
| tutorials = [[Kaveh Rahnema]] (time and place t.b.a.) | | tutorials = [[Kaveh Rahnema]] (time and place t.b.a.) <br> Monday 10-12, lecture room MI 02.07.023, <br/>First Tutorial: April 14 | ||
| exam = written exam <!-- '''Oct 14, 10.00-11.30''' in lecture hall '''MI HS 2''' --> | | exam = written exam <!-- '''Oct 14, 10.00-11.30''' in lecture hall '''MI HS 2''' --> | ||
| tumonline = [https://campus.tum.de/tumonline/lv.detail?clvnr=950138649 Scientific Computing II] | | tumonline = [https://campus.tum.de/tumonline/lv.detail?clvnr=950138649 Scientific Computing II] | ||
Revision as of 08:36, 17 March 2014
- 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
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 ...
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.
- V. Eijkhout: Introduction to High-Performance Scientific Computing (textbook, available as PDF on the website)
- 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 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/