Scientific Computing I - Winter 11: Difference between revisions

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* October 27: [http://www5.in.tum.de/lehre/vorlesungen/sci_comp/ws11/slides/01_discipline.pdf Introduction], Further Reading: [http://www.deixismagazine.org/2011/04/a-long-view-of-gulf-oil-spill/ A Real World Application Example]
* October 27: [http://www5.in.tum.de/lehre/vorlesungen/sci_comp/ws11/slides/01_discipline.pdf Introduction], Further Reading: [http://www.deixismagazine.org/2011/04/a-long-view-of-gulf-oil-spill/ A Real World Application Example]
* November 3: [http://www5.in.tum.de/lehre/vorlesungen/sci_comp/ws11/slides/02_fibonacci.pdf Population Modelling - Discrete Models], Further Reading:[http://plato.stanford.edu/entries/models-science/ Models in Science (Stanford Encyclopedia of Philosophy)]  
* November 3: [http://www5.in.tum.de/lehre/vorlesungen/sci_comp/ws11/slides/02_fibonacci.pdf Population Modelling - Discrete Models], Further Reading:[http://plato.stanford.edu/entries/models-science/ Models in Science (Stanford Encyclopedia of Philosophy)]  
* November 10:
* November 10: [http://www5.in.tum.de/lehre/vorlesungen/sci_comp/ws11/slides/03_population.pdf Population Modelling - ODEs], Further Reading:  
* November 24:
* November 24:
* December 1:
* December 1:

Revision as of 14:57, 22 September 2011

Term
Winter 11
Lecturer
Dr. rer. nat. habil. Miriam Mehl
Time and Place
Thursday, 10:00-12:00;
Audience
Computational Science and Engineering, 1st semester (Module IN2005)
Tutorials
-
Exam
written exam
Semesterwochenstunden / ECTS Credits
2 SWS (2V) / 3 Credits
TUMonline
{{{tumonline}}}



Announcements

Contents

This course provides an overview of scientific computing, i. e. of the different tasks to be tackled on the way towards powerful numerical simulations. The entire "pipeline" of simulation is discussed:

  • mathematical models: derivation, analysis, and classification
  • numerical treatment of these models: discretization of (partial) differential systems, grid generation
  • efficient implementation of numerical algorithms: implementation on monoprocessors vs. parallel computers (architectural features, parallel programming, load distribution, parallel numerical algorithms)
  • interpretation of numerical results & visualization
  • validation

The course Scientific Computing 1 is intended for students in the Master's Program Computational Science and Engineering and of the English-language programs of the Department of Computer Science. Students in all other study programs, please consider our lecture Modellbildung und Simulation (see the lecture from summer term 2008, for example), instead.

Lecture Notes and Material

Exams

Literature

Books and Papers

  • B. DiPrima: Elementary Differential Equations and Boundary Value Problems, Wiley, 1992 (excellent online material)
  • A.B. Shiflet and G.W. Shiflet: Introduction to Computational Science, Princeton University Press (in particular Chapter 3,5,6)
  • G. Golub and J. M. Ortega: Scientific Computing and Differential Equations, Academic Press (in particular Chapter 1-4,8)
  • D. Braess: Finite Elements. Theory, Fast Solvers and Applications in Solid Mechanics, Cambridge University Press (in particular I.1, I.3, I.4, II.2)
  • Tveito, Winther: Introduction to Partial Differential Equations - A Computational Approach, Springer, 1998 (in particular Chapter 1-4,7,10)


Online Material

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