Introduction to Scientific Computing

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Introduction to Scientific Computing
(winter 2002/2003)

Dr. Miriam Mehl

Announcements:

midterm exam: 19.12.2002 during the tutorial
final exam: 14.02.2003 ,
final exam -- repetition: 25.04.2003, 14.00 h - 16.00 h, room 02.07.023
A further (oral or written) repetition is not possible!!! If you did not pass the exams, you have to take part in next years exams.
Results of the repetition exam will available on monday, May 6th, 12:00 h on our announcement boards.

Audience:

students in Computational Science and Engineering (CSE, compulsory course)

Time and Place:

Monday 13-15, lecture room 02.07.023, first lesson 21.10.2002

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:

Midterm Exam, Solution

Final Exam, Solution

Lesson 1: What is Scientific Computing? (Handout)

Lesson 2: Mathematical Modells 1 (Handout)

Lesson 3: Mathematical Modells 2: ODE (Handout)

Lesson 4: Mathematical Modells 3: PDE (Handout)

Lesson 5: Numerical Methods for ODE (Handout)

Lesson 6: Numerical Methods for PDE (Handout)

Lesson 7: Iterative Solvers for SLE (Handout)

Lesson 8: Fast Iterative Solvers for SLE (Handout)

Lesson 9: Implementation (Handout)

Lesson 10: Grids (Handout)

Lesson 11: Visualization (Handout)

Tutorial:

Dr. Sergey Pankratov

Thursday 14-16, lecture room 02.07.023, first tutorial 31.10.2002

Maple (ppt-slides)

Maple Worksheets:

Introduction to Maple: worksheet, html

Mathematical Models: Examples for ODEs and PDEs: worksheet, html, worksheet including solutions, html including solutions

Numerical Treatment of Mathematical Models: worksheet, html, worksheet including solutions, html including solutions

Iterative Solution of Linear Systems of Equations 1: worksheet, html

Iterative Solution of Linear Systems of Equations 2: worksheet html

Miriam Mehl