Introduction to Scientific Computing (winter 2001/2002): Difference between revisions
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'''Lecture Notes and other Course Material:''' | '''Lecture Notes and other Course Material:''' | ||
* Lesson 1: ''What is Scientific Computing?'' {{pdf|PDF | * Lesson 1: ''What is Scientific Computing?'' {{pdf|scico_wi01_lesson1|PDF}} (4932K) | ||
* Lesson 2: ''Tools: Libraries and Software'' PDF (1404K) | * Lesson 2: ''Tools: Libraries and Software'' PDF (1404K) | ||
* Lesson 3: ''Principles of Mathematical Modelling'' PDF (1544K) | * Lesson 3: ''Principles of Mathematical Modelling'' PDF (1544K) | ||
Revision as of 09:31, 16 May 2008
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This lecture is joint work with the lecture Introduction to Scientific Computing, given at the University of Stuttgart.
Audience: Students in [Computational Science and Engineering] (CSE, compulsory course)
Time and Place: Wednesday 10:15-11:45, lecture hall 2705A
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. Starting from mathematical models (derivation, analysis, and classification; various examples), their numerical treatment is discussed (discretization of differential systems, grid generation). The next chapter deals with the efficient implementation of numerical algorithms, both on monoprocessors and parallel computers (architectural features, parallel programming, load distribution, parallel numerical algorithms). Finally, some remarks on the interpretation of numerical results (visualization) are made. The course is conceived as an introduction to the thriving field of numerical simulation for computer scientists, mathematicians, engineers, or natural scientists without an already strong background in numerical methods.
Lecture Notes and other Course Material:
- Lesson 1: What is Scientific Computing? Error creating thumbnail: Unable to save thumbnail to destination PDF (4932K)
- Lesson 2: Tools: Libraries and Software PDF (1404K)
- Lesson 3: Principles of Mathematical Modelling PDF (1544K)
- Lesson 4: Continuous Models 1: ODE PDF (952K)
- Lesson 5: Continuous Models 2: PDE PDF (1000K)
- Lesson 6: Numerical Treatment of ODE PDF (1116K)
- Lesson 7: Numerical Treatment of ODE PDF (1240K)
- Lesson 8: Standard Iterative Solvers of SLE PDF (968K)
- Lesson 9: Fast Iterative Solvers of SLE PDF (692K)
- Lesson 10: Implementation: Target Architectures PDF (908K)
- Lesson 11: Implementation: Parallelization PDF (832K)
- Lesson 12: Grid Generation and Refinement PDF (836K)
- Lesson 13: Interpreting the Results: Visualization PDF (728K)
- Lesson 14: Case Study: CFD PDF (660K)
