Introduction to Scientific Computing (winter 2001/2002)

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Cse.jpg

Prof. Dr. Chr. Zenger

Prof. Dr. H.-J. Bungartz

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? Pdf.jpg PDF (4932K)
  • Lesson 2: Tools: Libraries and Software Pdf.jpg PDF (1404K)
  • Lesson 3: Principles of Mathematical Modelling Pdf.jpg PDF (1544K)
  • Lesson 4: Continuous Models 1: ODE Pdf.jpg PDF (952K)
  • Lesson 5: Continuous Models 2: PDE Pdf.jpg PDF (1000K)
  • Lesson 6: Numerical Treatment of ODE Pdf.jpg PDF (1116K)
  • Lesson 7: Numerical Treatment of ODE Pdf.jpg PDF (1240K)
  • Lesson 8: Standard Iterative Solvers of SLE Pdf.jpg PDF (968K)
  • Lesson 9: Fast Iterative Solvers of SLE Pdf.jpg PDF (692K)
  • Lesson 10: Implementation: Target Architectures Pdf.jpg PDF (908K)
  • Lesson 11: Implementation: Parallelization Pdf.jpg PDF (832K)
  • Lesson 12: Grid Generation and Refinement Pdf.jpg PDF (836K)
  • Lesson 13: Interpreting the Results: Visualization Pdf.jpg PDF (728K)
  • Lesson 14: Case Study: CFD Pdf.jpg PDF (660K)

Block Tutorials:

Prof. Dr. Hans-Joachim Bungartz (University of Stuttgart) and Dr. Stefan Zimmer (University of Stuttgart)

Date Time Room Worksheet
Oct 26th (Friday) 15:00-18:00 0406 Mws.jpg tutorial.mws
Nov 16th (Friday) 15:00-18:00 0406 Mws.jpg diffeq.mws and Mws.jpg worksheet including solutions
Dec 12th (Wednesday) 15:00-18:00 0406 Mws.jpg diffnum.mws and Mws.jpg worksheet including solutions
Jan 18th (Friday) 15:00-18:00 0406 Mws.jpg linsolv.mws and the Mws.jpg worksheet from the tutorial of Feb 1st

The four block tutorials will take place in the multimedia room (room number 0406) of the Institute for Communication Networks.


Weekly tutorials:

Dr. Stefan Zimmer (University of Stuttgart)

Time and place: Friday, 8:30-10:00, seminar room 1237

Topics:

date Tutorial
Feb 1st After some confusion about the tutorial last week, there will be another tutorial for questions about the worksheet on iterative methods (8:30-10:00 - if the train from Stuttgart arrives in time, some minutes later if it does not - room 1237)
Feb 8th (Friday) Deadline for submission of the exercises

Submission of exercises: please send an email to Stefan Zimmer (zimmer@in.tum.de) and attach the Maple worksheet containing your solutions to the exercises.

Final Exam:

The Final Exam in Scientific Computing will be on Thursday, February, 28th at 14:00-16:00 in room 1229.

As the midterm exam, it will consist of one part (30 minutes) with questions tat have to be answered without notes, books etc., and of a second part (90 minutes) for which notes and books are allowed, but no calculators etc. It will cover the contents of the lectures up to and including Lesson 9 'Fast iterative solvers of SLE'.