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.

Location

HLRS, University of Stuttgart
Nobelstraße 19
70569 Stuttgart, Germany
Room 0.439 / Rühle Saal
Location and nearby accommodations

Registration

Location

HLRS, University of Stuttgart
Nobelstraße 19
70569 Stuttgart, Germany
Room 0.439 / Rühle Saal
Location and nearby accommodations

Start date

Oct 19, 2026
08:30

End date

Oct 23, 2026
17:00

Language

English

Entry level

Basic

Course subject areas

Parallel Programming

Topics

MPI

OpenMP

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Prerequisites and content levels

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.

Instructors

Dr. Tobias Haas, Dr.-Ing. Christoph Niethammer und Lucienne Dettki

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.

Expand list of skills

Software Development (SD)
SD1.2.1 – Parallel Algorithms
SD1.2.2 – Shared Memory Systems
SD1.2.3 – Message Passing Systems
SD1.3 – Efficient Algorithms and Data Structures
SD2.2 – Debugging

HPC Knowledge (K)
K3.1 – Level of Parallelization
K3.2 – Parallelization Overheads
K3.3 – Domain Decomposition
K2.1 – Performance Frontiers
K1.2.2 – Network
K1.3.1.5.1 – MPI-IO

Performance Engineering (PE)
PE2 – Measuring System Performance
PE2.1 – Utilisation Principles
PE2.3 – Profiling Tools
PE3.3 – Strong vs. Weak Scaling
PE5 – Optimization Principles

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

0 €: Employees of the High Performance Computing Center Stuttgart (HLRS), Jülich Supercomputing Centre (JSC), or Leibniz Supercomputing Centre (LRZ)
50 €: Students without a completed master's degree (or equivalent)
110 €: PhD students or employees at German universities or public research institutes
215 €: PhD students or employees at universities or public research institutes in EU, EU-associated, or PRACE countries (excluding Germany)
430 €: PhD students or employees at universities or public research institutes outside EU, EU-associated, and PRACE countries
730 €: Government and public administration employees (non-research)
1150 €: Private sector (industry, companies, freelancers)

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

Contact

Lucas Jordan phone +49 711 685-87206, training(at)hlrs.de

HLRS Training Collaborations in HPC and AI

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. SIDE is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC.
Since 2025, HLRS has been coordinating one of the AI Factories of the EuroHPC JU: HammerHAI.