Introduction to Scientific Computing II - Summer 12

Term

Summer 12

Lecturer

Univ.-Prof. Dr. Michael Bader

Time and Place

lecture room MI 02.07.023, time: t.b.a.

Audience

Computational Science and Engineering, 2nd semester (Module IN2141)

Tutorials

Wolfgang Eckhardt lecture room MI 02.07.023, time: t.b.a.

Exam

written exam

Semesterwochenstunden / ECTS Credits

2V + 1Ü / 4 Credits

TUMonline

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Contents

This course provides a deeper knowledge in two important fields of scientific computing:

• solution of large sparse systems of linear equations:
  • Gaussian elemination
  • relaxation methods
  • multigrid methods
  • steepest descent
  • conjugate gradient methods
• molecular dynamics simulations
  • the physical model
  • the mathematical model
  • approximations and discretization
  • implementational aspects
  • parallelisation
  • examples of nanofluidic simulations

The course is conceived for computer scientists, mathematicians, engineers, or natural scientists with already a background in the numerical treatment of (partial) differential equations.

Lecture Notes and Material

Annotated slides are available from the TeleTeachingTool Lecture Archive

lecture

material

tutorial

exercise

matlab

Literature

• William L. Briggs, Van Emden Henson, Steve F. McCormick. A Multigrid Tutorial. Second Edition. SIAM. 2000.
• J.R. Shewchuk. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain. Edition 1.25. 1994.
• M. Griebel, S. Knapek, G. Zumbusch, and A. Caglar. Numerische Simulation in der Molekulardynamik. Springer, 2004.
• 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 ASpplications. 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. Camebridge University Press, 1995.