Scientific Computing I - Winter 11

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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
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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


Lecture Notes and Material

October 20 no lecture (SET)
Introduction
Population Modelling - Discrete Models | Further Reading: A Real World Application Example
Models in Science (Stanford Encyclopedia of Philosophy)
Population Modelling - ODEs | Further Reading:
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no lecture, Dies Academicus |
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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