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 the RWTH’s IT Center. It might be helpful to read through the information which is provided during the HPC introduction on February 5th and 6th 2024. This is especially true if you want to actively use CLAIX after this event.


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 nodes of the RWTH Compute Cluster 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. We also expect a growing number of application codes to combine MPI and OpenMP for clusters of nodes with a growing number of cores.

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. Also covered is hybrid parallelization, i.e., the combination of MPI and shared memory programming, which is gaining popularity as the number of cores per cluster node grows.

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 infrastructure that is equipped with powerful Intel Sapphire Rapid CPUs and NVIDIA H100 GPUs. 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.


  • 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.
  • You can/must register per topic, i.e., OpenMP (Mon + Tue), MPI (Wed + Thur), and ML/DL (Fri).

More details (e.g., agenda, material) can be found under:

Registration »