in cooperation with

 

Parallel Programming in Computational Engineering and Science (PPCES)

March 16th – 20th, 2026

This one week event will continue the tradition of previous annual week-long events that take place in Aachen every spring since 2001. We will cover the basics of parallel programming using OpenMP and MPI in Fortran and C/C++ and a first step towards performance tuning. Furthermore, we will embrace current topics in machine & deep learning. Hands-on exercises for each topic will be included.

The contents of the courses are generally applicable but will be specialized towards the compute cluster CLAIX which is the current system installed at RWTH’s IT Center. It might be helpful to read through the information which is provided during the HPC introduction on February 9th-10th 2025.

Topics

OpenMP is a widely used approach for programming shared memory architectures, supported by most compilers nowadays. We will cover the basics of the programming paradigm as well as some advanced topics such as programming NUMA machines. The compute nodes of the RWTH HPC Cluster (aka CLAIX) contain an increasing number of cores and thus we consider shared memory programming a vital alternative for applications that cannot be easily parallelized with MPI.

The Message Passing Interface (MPI) is the de-facto standard for programming large HPC systems. We will introduce the basic concepts and give an overview of some advanced features.

Machine & Deep Learning: We provide a fundamental introduction into machine and deep learning approaches as well as data processing techniques that support dataset preparation or model selection for training and inference. It covers the basic concepts for supervised and unsupervised learning such as classification, regression, and clustering to get a feeling which technique is appropriate for a particular problem. Additionally, we conduct several hands-on exercises with common frameworks such as scikit-learn and PyTorch on our recent HPC Cluster CLAIX. In these exercises, we demonstrate how to define models, construct dataset and training pipelines or utilize monitoring and visualization of the training results, e.g., with Tensorboard. For the deep learning exercises, we start by training on a single GPU first. If that is not enough, we also show how to scale up distributed training onto multiple compute nodes or GPUs.

Organization

• There is no seminar fee.
• Presentations will be given in English. Slides will be available during or after the event.
• This is an in-person event and will be held on the RWTH IT Center premises (see below).
• You can/must register per day.
• For more details on the target audience, prerequistes and gained skills, see the “Skills” sections below (per topic).

Guest Speakers

We are happy to announce our guest speaker: Ruud van der Pas (Oracle Linux Engineering)

Agenda

Agenda is still subject to changes.

Day 1 + 2: OpenMP

Monday, March 16	Day 1: OpenMP Part I
09:00 – 09:10	Welcome & Organization	Christian Terboven (RWTH)
09:10 – 10:10	Introduction into Parallel Computing	Ruud van der Pas (Oracle Linux Engineering)
10:10 – 10:40	Coffee Break
10:40 – 12:10	OpenMP Basics – Part 1 Overview Parallel Region Worksharing Scoping	Christian Terboven (RWTH)
12:10 – 13:30	Lunch Break (on your own)
13:30 – 14:30	OpenMP Basics – Part 2 Compilers + Exercises	Christian Terboven (RWTH)
14:30 – 15:30	OpenMP Basics – Part 3 (incl. Lab) Agenda Tasking Motivation Tasking Model Taskloop Cutoff Dependencies	Christian Terboven (RWTH)
15:30 – 16:00	Coffee Break
16:00 – 17:00	OpenMP Basics – Part 4 (incl. Lab) Agenda NUMA Affinity Hybrid	Christian Terboven (RWTH)

 

Day 3+4: MPI

Wednesday, March 18	Day 3: MPI Part I
09:00 – 09:10	Welcome & Organization	Marc-André Hermanns (RWTH)
09:10 – 10:30	MPI Basics (incl. Lab) MPI Basics MPI Concepts	Marc-André Hermanns (RWTH)
10:30 – 11:00	Coffee Break
11:00 – 12:30	Blocking Point-to-Point Communication – Part 1 (incl. Lab)	Marc-André Hermanns (RWTH)
12:40 – 14:00	Lunch Break (on your own)
14:00 – 15:30	Blocking Point-to-Point Communication – Part 2 (incl. Lab)	Marc-André Hermanns (RWTH)
15:30 – 16:00	Coffee Break
16:00 – 17:00	Non-blocking Point-to-Point Communication (incl. Lab)	Marc-André Hermanns (RWTH)

 

Thursday, March 19	Day 4: MPI Part II
09:00 – 10:30	Derived Datatypes (incl. Lab)	Marc-André Hermanns (RWTH)
10:30 – 11:00	Coffee Break
11:00 – 12:30	Blocking Collective Communication (incl. Lab)	Marc-André Hermanns (RWTH)
12:30 – 14:00	Lunch Break (on your own)
14:00 – 15:30	Communicator Basics (incl. Lab)	Marc-André Hermanns (RWTH)
15:30 – 16:00	Coffee Break
16:00 – 17:00	Hybrid programming	Marc-André Hermanns (RWTH)

Day 5: Machine & Deep Learning

Friday, March 20	Day 5: Machine Learning
09:00 – 10:30	Introduction to AI and Machine Learning, and Preprocessing Techniques – Part 1	Jannis Klinkenberg (RWTH)
10:30 – 11:00	Coffee Break
11:00 – 12:30	Introduction to AI and Machine Learning, and Preprocessing Techniques – Part 2 (incl. Lab) Execution Options for ML/DL Software Hands-on Exercises (scikit)	Jannis Klinkenberg (RWTH)
12:30 – 14:00	Lunch Break (on your own)
14:00 – 15:30	Introduction to (Distributed) Deep Learning Introduction to Deep Learning Case Study – PyTorch Distributed Deep Learning + Case Study – PyTorch Further Links and Literature	Jannis Klinkenberg (RWTH)
15:30 – 16:00	Coffee Break
16:00 – 17:00	Hands-on (PyTorch)	Jannis Klinkenberg (RWTH)

 

Skills – OpenMP

Course level

beginner

Target audience

• HPC users
• HPC developers

Prerequisites

• Able to understand C/C++ (or Fortran) source codes
• Comfortable with C/C++ or Fortran programming (for lab sessions)
• Comfortable using a Linux environment (for lab sessions)

Gained skills

• Broad knowledge of OpenMP, including the machine, memory and execution model
• General understanding when and how to use the different worksharing, synchronization and tasking constructs and directives
• Capability to apply OpenMP to existing codes and to use the scoping correctly
• Understanding of how OpenMP parallel programs interact with the system, in particular of NUMA architectures and SIMD microarchitectures

Skills – MPI

Course level

beginner

Target audience

• HPC developers

Prerequisites

• Able to understand C/C++ (or Fortran) source codes
• Comfortable with C/C++ or Fortran programming (for lab sessions)
• Comfortable using a Linux environment (for lab sessions)

Gained skills

• General understanding of the classic MPI “world model” of process initialization
• Overview of point-to-point and collective communication an their use cases
• Understand the use and definition of MPI derived datatypes
• Knowledge of basic MPI terminology
• Knowledge of blocking and non-blocking procedure calls and when to use them
• Using MPI together with OpenMP in basic hybrid scenarios

Skills – ML/DL

Course level

• beginner to intermediate

Target audience

• HPC/AI users
• HPC/AI developers

Prerequisites

• Basic knowledge of Python
• Comfortable using a JupyterHub or Linux environment (for lab sessions)
• Comfortable with Python programming and a little Bash scripting (for lab sessions)

Gained skills

• High-level overview of data proprocessing, AI, machine and deep learning techniques and how they relate to each other
• Understanding how to apply shallow ML techniques to solve classification and clustering tasks
• Understanding how to execute PyTorch deep learning and distributed deep learning on HPC infrastructures

Material Downloads

Materials will be published during and after the workshop.

OpenMP Exercises

• coming soon

MPI Exercises

• coming soon

ML/DL Exercises

• coming soon

Location

The workshop will take place in-person on the premises of the IT Center of RWTH Aachen University at:

Seminar rooms 003/004
Kopernikusstraße 6
52074 Aachen

Registration

Registration link (via our NHR4CES website): coming soon

Please also withdraw your registration in the registration system using the link that you got in your confirmation e-mail (or let us know) if you cannot attend anymore. That will help us a lot in preparing the event (seats, catering and so on). Thanks! (Here are further instructions how to change or cancel your registration.)

Registration closing date: March 9th, 2026

Further Links

Need support or want to ask questions?

• HPC Consultation Hour (once per month)
• AI/ML/DL Consultation Hour (once per week)

Want to apply for compute time (proposals)?

• Overview of Compute Project Categories
• Visit WestAI website and send mail to contact@westai.de