Overview HPC for AI

In recent years artificial intelligence became an importance tool for many scientific domains. Various problems are tackled using methods from both classical machine learning and modern deep learning. These include but are not limited to challenges from

  • Medicine (e.g. tumor dectection in MRT scans)
  • Biology (e.g. segmentation of cells in microscopy)
  • Chemistry (e.g. predicting molecule properties)
  • Digital Humanities
  • Earth System Sciences
  • Forestry

The data types used for artificial intelligence methods are vast, encompassing images, videos, audio, graphs and point clouds. HPC systems enable the analysis of large data sets and the training of state-of-the-art models. Our software stack and hardware is optimized to increase the performance (speed) of the training while keeping the quality of the results the same.


We offer various services connected to artificial intelligence. Please contact us if you have a use case and we will discuss how to proceed individually.

Software and Libraries

Our HPC systems have a number of software tools installed. Examples are:

  • Anaconda for Python users
  • MPI
  • Cuda
  • Tensorflow
  • PyTorch

If your desired software libraries is not available, feel free to contact us.


We can support you on a wide range of common issues:

  • Exploring the potential benefits of HPC systems from AI workflows
  • Transferring AI workflows to HPC systems (e.g. parallelization and optimization)
  • Profiling applications to identify bottlenecks

Additionally, you can check out our other domain specific services linked above.


The GWDG operates multiple HPC systems. Two systems are available to universities and publicly funded research institutes:

  • SCC: The SCC is available to members of the University of Göttingen and the Max Planck Institutes.
  • Emmy: Access to Emmy is granted based on a project basis

Information on how to access the HPC systems can be found here.

If you have any questions, feel free to contact us.