Scientific Computing II - Summer 15: Difference between revisions

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== Lecture Slides ==
== Lecture Slides ==


* [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/scicomp2_overview.pdf Introduction], [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss14/smoothing.pdf Relaxation Methods] (Apr 14)
* [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/scicomp2_overview.pdf Introduction], [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/smoothing.pdf Relaxation Methods] (Apr 14)


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Revision as of 07:10, 17 April 2015

Term
Summer 2015
Lecturer
Prof. Dr. Michael Bader
Time and Place
Monday 14-16, lecture room MI HS 2
First Lecture: Tue, Apr 14, MI 00.08.038
Audience
Computational Science and Engineering, 2nd semester
others: see module description
Tutorials
Arash Bakhtiari
Wednesday 14-16, lecture room MI 00.08.038,
First Tutorial: Apr 17
Exam
written exam at end of semester
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
  • molecular dynamics simulations
    • the physical model
    • the mathematical model
    • approximations and discretization
    • implementational aspects
    • parallelisation
    • examples of nanofluidic simulations

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 Notes and Material

All further announcements, worksheets and information can be found on the Moodle-page of this course.

Lecture Slides


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. Camebridge University Press, 1995.

Further Material

Annotated slides for the lecture in summer 2010 /(given by Dr. Tobias Weinzierl) are available from the TeleTeachingTool Lecture Archive

Matlab (together with installation instructions) is available from https://matlab.rbg.tum.de/

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