Iterative Linear Solvers and Parallelization

This course has been switched from hybrid to online-only.

The focus is on iterative and parallel solvers, and the parallel programming models MPI and OpenMP. Thereby, different modern Krylov Subspace Methods (CG, GMRES, BiCGSTAB, ...) as well as highly efficient preconditioning techniques are presented in the context of real life applications. Hands-on sessions (in C, Fortran and Python) will allow users to immediately test and understand the basic constructs of iterative solvers, the Message Passing Interface (MPI) and the shared memory directives of OpenMP (in C and Fortran). This course provides scientific training in Computational Science, and in addition, the scientific exchange of the participants among themselves. It is organized by HLRS, IAG and Uni. Kassel.


Online course
Organizer: HLRS, University of Stuttgart, Germany

Start date

Feb 19, 2024

End date

Feb 23, 2024



Entry level


Course subject areas

Programming Languages for Scientific Computing



Numerical Methods

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Prerequisites and content levels

  • Monday+Tuesday: Unix / C or Fortran (MPI: or Python)
  • Wednesday-Friday: Basics of linear algebra / MATLAB or GNU Octave
Content levels:
  • Basic: 14 hours 15 minutes
  • Intermediate: 45 minutes
  • Community: 15 hours

Learn more about course curricula and content levels.


Participants are expected to use their own machines or institute clusters.

  • For the iterative solvers part of the course, a recent version of MATLAB or GNU OCTAVE (available for free) should be installed.

  • For the MPI and OpenMP part of the course, Linux command shell commands and some basic programming knowledge in C or Fortran (or Python for the MPI part).

    To be able to do the hands-on exercises, you need a computer with an OpenMP capable C/C++ or Fortran compiler and a corresponding up-to-date MPI library (in case of Fortran, the mpi_f08 module is required). In addition, you can perform the MPI exercises in Python with mpi4py + numpy. In this case, an appropriate installation on your system is required (together with a C/C++ or Fortran installation for the OpenMP exercises).

    To check if your MPI and OpenMP installation is valid, please either

    • download TEST.tar.gz from this link and run tar -xvzf TEST.tar.gz or
    • download from this link and run unzip

    After that follow the instructions in TEST/README.txt within the archive.

Please make sure to have a functioning working environment / access to an HPC cluster prior to the start of the course.


Refer to the detailed program.


Each participant will get a pdf of the slides.


Register via the button at the top of this page.
We encourage you to register to the waiting list if the course is full. Places might become available.

Registration closes on February 4, 2024.

Late registrations after the deadline are still possible according to the course capacity.


  • Students without master’s degree or equivalent: 40 Euro
  • PhD students or employees at a German university or public research institute: 90 Euro
  • PhD students or employees at a university or public research institute in an EU, EU-associated or PRACE country other than Germany: 180 Euro
  • PhD students or employees at a university or public research institute outside of EU, EU-associated or PRACE countries: 360 Euro
  • Other participants, e.g., from industry, other public service providers, or government: 960 Euro

Link to the EU and EU-associated (Horizon Europe), and PRACE countries.

Our course fees include coffee breaks (in classroom courses only).


Lucienne Dettki phone 0711 685 63894, dettki(at)

HLRS Training Collaborations in HPC

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC.

This course is provided within the framework of the bwHPC training program.

Further courses

See the training overview and the Supercomputing Academy pages.

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