Scientific Computing II - Summer 16: Difference between revisions

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{{Lecture
{{Lecture
| term = Summer 2016
| term = Summer 2016
| lecturer = [[Michael Bader]]
| lecturer = [[Michael Bader|Prof. Dr. Michael Bader]]
| timeplace = Lecture: tba
| timeplace = Monday 14-16 (MI HS 2); first lecture: Mon, Apr 11
:Tutorial: tba
| credits = 2V + 2Ü / 5 Credits
| credits = 6 SWS (4V + 2Ü) / 8 Credits
| audience = Computational Science and Engineering, 2nd semester <br> others: [https://campus.tum.de/tumonline/WBMODHB.wbShowMHBReadOnly?pKnotenNr=476730&pOrgNr=14189 see module description]
| audience = see [https://campus.tum.de/tumonline/WBMODHB.wbShowMHBReadOnly?pKnotenNr=456346&pOrgNr=14189 module description (IN2001)] in TUMonline
| tutorials = [[Carsten Uphoff, M.Sc.]] <br> Tuesdays 10-12, lecture room MI 02.07.023 (from Apr 12)
| tutorials = [[Emily Mo-Hellenbrand, M.Sc.]], [[Angelika Schwarz, M.Sc.]]
| exam = written exam, time/day see below
| exam = tba
| tumonline = [https://campus.tum.de/tumonline/LV.detail?clvnr=950238630 Scientific Computing II]
| tumonline =  
}}
}}


== News & Announcements ==
= Announcements =
* '''Extra session for questions:''' on Tuesday, July 26, in the tutorial slot (10-12 in room MI 02.07.023); opportunity to ask questions on all exam topics covered in the lectures


= Contents =


== What's ASC about? ==
This course provides a deeper knowledge in two important fields of scientific computing:


Many applications in computer science require methods of (prevalently numerical) mathematics - especially in science and engineering, of course, but as well in surprisingly many areas that one might suspect to be directly at the heart of computer science:
* 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.


Consider, for example, Fourier and wavelet transformations, which are indispensable in image processing and image compression. Space filling curves (which have been considered to be "topological monsters" and a useless theoretical bauble at the end of the 19th century) have become important methods used for parallelization and the implementation of data bases. Numerical methods for minimization and zero-setting are an essential foundation of Neural Networks in machine learning.
== Lecture Slides ==


Essentially, these methods come down to the question of how to represent and process information or data as (multi-dimensional) continuous functions.  
Lecture slides will be published here as soon as they become available. For future lectures, the respective slides from summer 2015 will be linked.
Algorithms of Scientific Computing (former Algorithmen des Wissenschaftlichen Rechnens) provides a generally understandable and algorithmically oriented introduction into the foundations of such mathematical methods. Topics are:
* [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/scicomp2_overview.pdf Introduction], [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/smoothing.pdf Relaxation Methods] (Apr 11, 18)
* [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/multigrid.pdf Multigrid Methods] (Part I: Apr 18; Part II: Apr 25, May 2, Part III: May 2, 9)
** [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss13/MG-illustration.pdf some multigrid animations] (more peas!)
** if you're interested: [http://wwwhome.math.utwente.nl/~botchevma/fedorenko/index.php On the history of the Multigrid method creation] (website article by R.P. Fedorenko)
* [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/conjugate.pdf Steepest Descent and Conjugate Gradient Methods] (Part I&II: May 23, Part III: May 30 & Jun 6)
** additional material: [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/quadratic_forms.mws Maple worksheet quadratic_forms.mws], also as [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/quadratic_forms.pdf PDF]
** additional material: [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/conjugate_gradient.mws Maple worksheet conjugate_gradient.mws], also as [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/conjugate_gradient.pdf PDF]
<!--
* [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss15/biros-lecture-nbody-tum.pdf Guest lecture by George Biros on n-body methods]
-->
* Molecular Dynamics:
** [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/moldyn_intro.pdf Molecular Dynamics (Intro)] (Jun 13)
** [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/moldyn_model.pdf Molecular Dynamics (Modelling)] (Jun 13)
** [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/moldyn_numerics.pdf Molecular Dynamics (Time-Stepping)] (Jun 20)
** [http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss16/moldyn_forces.pdf Molecular Dynamics (Force Computation: Linked Cell, Barnes-Hut, Fast Multipole)] (Jun 20, 27; Jul 4)
*** additional material: [http://epubs.siam.org/doi/abs/10.1137/0913055 article by Anderson: An implementation of the fast multipole method without multipoles] (PDF can be accessed via LRZ proxy or after logging in to TUM's e-library)


* The fast Fourier transformation (FFT) and some of its variants:
== Exercises ==
** FCT (Fast Cosine Transform), real FFT, Application for compression of video and audio data
See [//www.moodle.tum.de/course/view.php?id=25898 Moodle] course.
* Space filling curves (SFCs):
** Construction and properies of SFCs
** Application for parallelization and to linearize multidimensional data spaces in data bases
* Hierarchical and recursive methods in scientific computing
** From Archimede's quadrature to the hierarchical basis
** Cost vs. accuracy
** Sparse grids, wavelets, multi-grid methods


== Lecture Slides and Supplementary Materials ==
= Repeat Exam =


Lecture slides will be published here as soon as they become available.
* '''Exam Review''': Wednesday, Oct 26, 15.00-17.00 (office E.2.048 in Leibniz Supercomputing Centre, Boltzmannstr. 1)
* written exam
* Date: '''Monday, Oct 10'''
* Time: '''8.00-9.45''' - Please make sure to be in the lecture hall by 7.45, as the exam will start precisely at 8.00.
* Place: '''Interim 2''' (black building in front of math/informatics)
* material: '''no helping material of any kind is allowed during the exam'''
* Topics: everything that was covered in the lectures and tutorials <!-- (except the last lecture, on long-range forces, July 17) -->
<!-- * '''extra session for questions''' concerning the exam on '''Tue, July 26, from 10.15''' in room MI 02.07.023 -->


<B> Please make sure that you are registered for the exam via TUMOnline!</B>


== Worksheets and Solutions ==
Old exams are available on the websites of the last years (note that the curriculum of the lecture has slightly changed since then!):
[http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss11/exam.pdf]
[http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss10/exam.pdf]
[http://www5.in.tum.de/lehre/vorlesungen/sci_compII/ss08/exam.pdf]


Assignment sheets will be posted here. All in good time.
= Literature =
 
 
=== IPython Notebook ===
* If you want to use a local installation of IPython Notebook on your laptop or home computer, just refer to [http://ipython.org/notebook.html the IPython Notebook website] on how to install IPython Notebook on Linux, Windows or MAC platforms
** If you install IPython Notebook for Windows, it might happen that starting it from the "Start" menue will open an IPython server website, but that you cannot create or import any new Python notebooks. In that case, try to start IPython Notebook from the command line via "ipython notebook --notebook-dir=.\" (from the directory where you want to store the Python notebooks); you can also create a batch file for this ([http://www5.in.tum.de/lehre/vorlesungen/asc/ss13/startNotebook.bat download example], place it in the desired directory).
 
 
== Literature and Additional Material ==
 
Books that are labeled as "available as e-book" can be accessed as e-book via the TUM library - see the [http://www.ub.tum.de/ebooks ebooks website] of the library for details on how to access the books.
 
=== Fast Fourier Transform: ===
The lecture is oriented on:
* ''W.L. Briggs, Van Emden Henson'': [http://epubs.siam.org/doi/book/10.1137/1.9781611971514 The DFT - An Owner's Manual for the Discrete Fourier Transform], SIAM, 1995 (available as e-book)
*  ''Thomas Huckle, Stefan Schneider'': Numerische Methoden - Eine Einführung für Informatiker, Naturwissenschaftler, Ingenieure und Mathematiker, Springer-Verlag, Berlin-Heidelberg, 2.Auflage 2006 (German only)
* ''Charles van Loan'': [http://epubs.siam.org/doi/book/10.1137/1.9781611970999 Computational Frameworks for the Fast Fourier Transform], SIAM, 1992 (available as e-book)
 
=== Hierarchical Methods and Sparse Grids ===
* [http://www5.in.tum.de/lehre/vorlesungen/algowiss2/Bungartz_HierVerf.ps.gz Skript of H.-J. Bungartz for the lecture "Rekursive Verfahren und hierarchische Datenstrukturen in der numerischen Analysis"] (German only)
* [http://www5.in.tum.de/pub/bungartz04sparse.pdf General overview paper on Sparse Grids]
* Chapter on Sparse Grids in [http://www5.in.tum.de/pub/pflueger10spatially.pdf this book]
 
=== Wavelets ===
* ''E. Aboufadel, S. Schlicker'': [http://faculty.gvsu.edu/aboufade/web/wavelets/book.htm Discovering Wavelets], Whiley, New York, 1999 (available as e-book).
** [http://faculty.gvsu.edu/aboufade/web/wavelets/tutorials.htm Collection of Wavelet tutorials] (maintained by E. Aboufadel and S. Schlicker)
* ''[http://people.uwec.edu/walkerjs/ J.S. Walker]'': [http://people.uwec.edu/walkerjs/Primer/ A Primer on Wavelets and their Scientific Applications, Second Edition], Chapman and Hall/CRC, 2008.
* ''[http://people.uwec.edu/walkerjs/ J.S. Walker]'': Wavelet-based Image Compression ([http://people.uwec.edu/walkerjs/media/WBIP.pdf download as PDF])
 
=== Space-filling Curves: ===
* ''Michael Bader'': [http://www.space-filling-curves.org Space-Filling Curves - An introduction with applications in scientific computing], Texts in Computational Science and Engineering 9, Springer-Verlag, 2012<br>( [http://link.springer.com/book/10.1007/978-3-642-31046-1/page/1 available as eBook], also in the TUM library)
* ''Hans Sagan'': Space-Filling Curves, Springer-Verlag, 1994


* 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)
* [http://www.cs.cmu.edu/~jrs/ J.R. Shewchuk]. An Introduction to the Conjugate Gradient Method Without the Agonizing Pain ([http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf download as PDF]). 1994.
* V. Eijkhout: [http://tacc-web.austin.utexas.edu/veijkhout/public_html/istc/istc.html 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.


[[Category:Teaching]]
[[Category:Teaching]]

Latest revision as of 08:56, 19 October 2016

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 see below
Semesterwochenstunden / ECTS Credits
2V + 2Ü / 5 Credits
TUMonline
Scientific Computing II



Announcements

  • Extra session for questions: on Tuesday, July 26, in the tutorial slot (10-12 in room MI 02.07.023); opportunity to ask questions on all exam topics covered in the lectures

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.

Exercises

See Moodle course.

Repeat Exam

  • Exam Review: Wednesday, Oct 26, 15.00-17.00 (office E.2.048 in Leibniz Supercomputing Centre, Boltzmannstr. 1)
  • written exam
  • Date: Monday, Oct 10
  • Time: 8.00-9.45 - Please make sure to be in the lecture hall by 7.45, as the exam will start precisely at 8.00.
  • Place: Interim 2 (black building in front of math/informatics)
  • material: no helping material of any kind is allowed during the exam
  • Topics: everything that was covered in the lectures and tutorials

Please make sure that you are registered for the exam via TUMOnline!

Old exams are available on the websites of the last years (note that the curriculum of the lecture has slightly changed since then!): [1] [2] [3]

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.
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