High Performance Computing II - summer term 2019

We will focus on a realistic model problem (rotor) in order to introduce the main topics of numerical methods for High Performance Computing.

First exercise class on Wednesday, April 24! Please enroll in moodle for this course!

Questions concerning the exercises/lab or the lecture, please contact Constantin Greif.

Contents

  • Architecture of Parallel Computers
  • Parallelization, MPI, Cuda
  • The Cluster Pacioli
  • Parallel Finite Elemente Method
  • Parallel Numerical Methods for Linear Systems of Equations
  • Domain Decomposition
  • Parallel Preconditioning
  • Parallel Multigrid Methods
  • Symmetric Eigenvalue Problems
  • Storage Formats for Sparse Matrices

Information

Responsible
  • Prof. Dr. Stefan Funken;
  • Prof. Dr. Karsten Urban;
  • (M.Sc. Constantin Greif)

Type

Lecture, Exercises, Lab (2/2/2), i.e. 8 credits (Master)

Lecture

Monday 8:00 - 10:00; Heho18 - 120 

Exercises and Lab

Wednesday 16:00 - 20:00; Heho18 - E60

 

Courses
  • Master CSE
  • Mathematik (Bachelor and Master)
  • Wirtschaftsmathematik (Bachelor and Master)
  • Mathematische Biometrie (Bachelor and Master)
  • Physik (Master)
  • Wirtschaftsphysik (Master)

Exam        The exam will be a project at the end of the semester.

Lectures

  1.  April 29: PDE model problem.

  2.  May 06: FEM realization in MATLAB.

  3.  May 13: Sparse Matrix data formats and uniform refinement.

  4.  May 20: Direct & Iterative Methods.

  5. May 27: Multiscale methods 1.

  6. June 03: Multiscale methods 2.

  7. June 17: Partitioning and coloring methods.

  8. June 24: Domain decomposition 1.

  9. July 01: Domain decomposition 2.

  10. July 08: Parallel solvers.

  11. July 15: Domain decomposition 3.

Resources

Literature:

  • G. Alefeld, I. Lenhardt, H. Obermaier, Parallele numerische Verfahren, Springer 2002

Online:

Contact

Prof. Dr. Stefan Funken
Helmholtzstr. 20
Room 1.08

Prof. Dr. Karsten Urban
Helmholtzstr. 20
Room 1.12

M. Sc. Constantin Greif
Helmholtzstr. 20
Room 1.28