Scientific Computing II - Summer 16
- Term
- Summer 2016
- Lecturer
- Prof. Dr. Michael Bader
- Time and Place
- Monday 14-16 (MI HS 2); first lecture: Mon, Apr 11
- Audience
- Computational Science and Engineering, 2nd semester
others: see module description - Tutorials
- Carsten Uphoff, M.Sc.
Tuesdays 10-12, lecture room MI 02.07.023 (from Apr 12) - Exam
- written exam, time/day t.b.a.
- Semesterwochenstunden / ECTS Credits
- 2V + 2Ü / 5 Credits
- TUMonline
- Scientific Computing II
Contents
This course provides a deeper knowledge in two important fields of scientific computing:
- iterative solution of large sparse systems of linear equations:
- relaxation methods
- multigrid methods
- steepest descent
- conjugate gradient methods
- preconditioning
- molecular dynamics simulations
- particle-based modelling (n-body simulation)
- algorithms for efficient force calculation
- parallelisation
The course is conceived for students in computer science, mathematics, or some field of science or engineering who already have a certain background in the numerical treatment of (partial) differential equations.
Lecture Slides
Lecture slides will be published here as soon as they become available. For future lectures, the respective slides from summer 2015 will be linked.
- Introduction, Relaxation Methods (Apr 11, 18)
- Multigrid Methods (Part I: Apr 18; Part II: Apr 25, May 2)
- some multigrid animations (more peas!)
- if you're interested: On the history of the Multigrid method creation (website article by R.P. Fedorenko)
- Steepest Descent and Conjugate Gradient Methods
- additional material: Maple worksheet quadratic_forms.mws, also as PDF
- additional material: Maple worksheet conjugate_gradient.mws, also as PDF
Exercises
See Moodle course.
Literature
- William L. Briggs, Van Emden Henson, Steve F. McCormick. A Multigrid Tutorial. Second Edition, SIAM, 2000 (available as eBook in the TUM library)
- Ulrich Trottenberg, Cornelis Oosterlee, Anton Schüller. Multigrid. Elsevier, 2001 (available as eBook in the TUM library)
- J.R. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain (download as PDF). 1994.
- V. Eijkhout: Introduction to High-Performance Scientific Computing (textbook, available as PDF on the website)
- M. Griebel, S. Knapek, G. Zumbusch, and A. Caglar. Numerical simulation in molecular dynamics. Springer, 2007 (available as eBook in the TUM library)
- M. P. Allen and D. J. Tildesley. Computer Simulation of Liquids. Oxford University Press, 2003.
- D. Frenkel and B. Smith. Understanding Molecular Simulation from Algorithms to Applications. Academic Press (2nd ed.), 2002.
- R. J. Sadus. Molecular Simulation of Fluids; Theory, Algorithms and Object-Orientation. Elsevier, 1999.
- D. Rapaport. The art of molecular dynamics simulation. Cambridge University Press, 1995.