🎓 Parallel Programming Workshop (MPI, OpenMP and Advanced Topics)

Distributed memory parallelization with the Message Passing Interface MPI (Mon, for beginners):
On clusters and distributed memory architectures, parallel programming with the Message Passing Interface (MPI) is the dominating programming model. The course gives an introduction to basic features available since MPI-1. Hands-on sessions (in C, Fortran, and Python) will allow users to immediately test and understand the basic constructs of the Message Passing Interface (MPI).

Shared memory parallelization with OpenMP (Tue, for beginners):
The focus is on shared memory parallelization with OpenMP, the key concept on hyper-threading, dual-core, multi-core, shared memory, and ccNUMA platforms. This course teaches shared memory OpenMP parallelization. Hands-on sessions (in C and Fortran) will allow users to immediately test and understand the directives and other interfaces of OpenMP. Race-condition debugging tools are also presented.

Intermediate and advanced topics in parallel programming (Wed-Fri):
Topics are advanced usage of communicators and virtual topologies, one-sided communication, derived datatypes,  MPI-2 parallel file I/O. MPI-3.0 introduced a new shared memory programming interface, which can be combined with MPI message passing and remote memory access on the cluster interconnect. It can be used for direct neighbor accesses similar to OpenMP or for direct halo copies, and enables new hybrid programming models. Several aspects of hybrid mixed model MPI+OpenMP parallelization are discussed in the MPI-4.1 and OpenMP-4.5(5.0) advanced topics.

Prerequisites

         Unix / C or Fortran (or Python for the MPI part)

Content levels

• Basic: 14 hours
• Intermediate: 12 hours
• Advanced: 10:30 hours
• Community: 0:45 hours

Learn more about course curricula and content levels.

Learning outcomes

Please refer to the course overview. This course provides scientific training in Computational Science, and in addition, the scientific exchange of the participants among themselves.

Skills earned

Expand the list below to see the list of skills teached during the course according to the skill tree provided by the HPC Certification Forum.

Agenda

All times are local times in the Central European Summer Time zone (Berlin). See link to detailed program (preliminary program)

Handouts

Each participant will get all slides as pdf and all exercises as tar.gz and zip archive. Most MPI exercises are (in addition to C and Fortran) also available for Python+mpi4py+numpy.

HLRS concept for on-site courses

Besides the content of the training itself, an important aspect of this event is the scientific exchange among the participants. We try to facilitate such communication by

• a social event on the evening of the first course day,
• offering common coffee and lunch breaks and
• working together in groups of two during the exercises. Laptops wil be provided.

Registration information

Apply for this course via the button at the top of this page. Registration closes on October 3, 2026.

Fees

• GCS Centre Employees: Employees of the HLRS, JSC, or LRZ: 0 €
• Students (pre-Master's): Students without a master's degree or equivalent: 50 € (If you select this option, please send your enrollment certificate to training(at)hlrs.de after applying.)
• Academia Germany: PhD students or employees at a German university or public research institute: 110 €
• Academia EU and Associated: PhD students or employees at a university or public research institute in an EU, EU-associated or PRACE country other than Germany: 215 €
• Academia Non-EU: PhD students or employees at a university or public research institute outside of EU, EU-associated or PRACE countries: 430 €
• Non-Academic Public Sector: Government, public administration, and public service providers (non-research): 730 €
• Other Participants: All participants not covered by the above categories, e.g., industry or self-employed: 1150 €

Link to the EU and EU-associated (Horizon Europe), and PRACE countries.
Our course fees include coffee breaks (in classroom courses).