By Lars Nondal

As mentioned in the previous article, CBS researchers might well need more computer power shortly.

How do I know? Because CBS researchers and students were very keen to jump on the wagon when the H100 GPU was first made available to them (on a smaller scale, of course) through the national HPC (High Performance Computing) services provided by DeiC earlier this year.

A few months ago, SDU eScience Center introduced 16 H100 GPU cores in DeiC Interactive HPC. So far, a substantial amount of these resources has been allocated to CBS, for free or, more precisely, paid for by the annual CBS contribution to DeiC. We still do not know the the Gefion computer cost model, but we expect that researchers and universities will have to bear a least some of the costs of running the system.

Increasing use of HPC at CBS
The H100 GPUs have already proved to be quite popular, even if they have never been advertised at CBS until now. The CBS RDM Support has received several grant applications for access to H100 GPUs from CBS researchers as well as master students writing their final thesis.

Without going too much into detail, we have listed some of the ongoing CBS projects using H100 GPUs on DeiC Interactive HPC (UCloud) right now:

  • Project(s) working with Quality Control (computer vision and image detection) in manufacturing, using the deep learning Yolo models (You Only Look Once).
  • Project working with Predictive Maintenance in Industry (sensor data, LSTM (Long Short-Term Memory) neural network)
  • Project working with applying Transformer architectures from NLP (Natural Language Processing) in financial time series forecasting and asset management.

The H100 GPUs are also being used in teaching. The course Artificial Intelligence and Machine Learning (Daniel Hardt/MSC, Nicolai Blegvad Thomsen/MSC) has a special setup with a version of Mistral, one of the largest available LLMs (Large Language Models), being downloaded and made available to students in the course, not for training or fine-tuning of the Mistral model - that would put too much demand on our limited pool of H100 GPU resources - but for inference/prompting via API and JupyterLab notebooks (Python).

Find out how to access DeiC Interactive HPC and how to apply for computing and storage resources

Check out our GitHub page for tutorials, guides, etc.

Please direct all questions to rdm@cbs.dk