By Lars Nondal
It was recently announced that Denmark is going to build one of the world’s most powerful AI supercomputers already this year. The name of the new supercomputer will be Gefion and the organization to run it will be the Danish Centre for AI Innovation.
The Danish Centre for AI Innovation is financed by The Novo Nordisk Foundation and the Export and Investment Fund of Denmark (EIFO) and will have CBS Chairman of the Board Torben Möger Pedersen as Chairman of the Board.
So, what exactly is it that is going to be built? And is it of any interest at all to CBS researchers?
Gefion is expected to be a “top 25 supercomputer”, referring to the bi-annual Top500 Ranking list. This means that it will not be in the absolute top but will still boast far more computer power than seen in Denmark before.
Essentially Gefion is a large GPU Cluster (Graphical Processing Unit), consisting of 1.528 GPU cores (H100 Tensor Core GPUs) from NVIDIA and with an extremely fast internal network combining the cores (Quantum-2 InfiniBand networking, 400 GB/s).
The H100 GPU is designed for large-scale AI and high-performance computing (HPC) workloads and is more than six times faster than the previous state-of-the-art A100 GPU.
Find out more about performance differences
The Danish Centre for AI Innovation’s cooperation with NVIDIA is not only about the infrastructure and the hardware but also includes access to NVIDIAs software platforms, training, and expertise.
There are no GPU clusters the size of Gefion or anywhere close available in any of the large university-driven supercomputers in Denmark (Computerome DTU/KU, Genome.dk/AU, Sophia/DTU). There are some GPUs available from SDU and AAU through DeiC Interactive HPC, including a small number of H100. See article below.
What makes GPUs so important for anything connected with AI and why cannot we simply rely on the traditional CPU (Central Processing Unit) computer?
According to professor Claudio Pica (Director of SDU eScience Center) “…The GPU contains thousands of small cores which can perform simple tasks many thousand times faster than a CPU…”. Click to learn more
The time-saving aspect of the performance of these supercomputers could prove very valuable to CBS researchers working with large dataset.
Can CBS researchers get access to the Gefion computer?
We are still waiting for more information about the access and cost model (the prices!) of the Gefion computer, but it is expected that companies and industry will have to pay more than universities and researchers.
At the presentation event, there was a lot of talk about the impact of the new computer on Danish research and innovation in engineering, life sciences, medicine, and other natural sciences, and not a lot of talk about the social sciences and humanities, but hopefully, access will be possible for researchers in Denmark regardless of discipline, if only the scientific quality of candidate research projects is deemed to be high enough.
But do CBS researchers need access?
Do social sciences & humanities researchers need that much computing power? A clear and distinct answer is probably. Not necessarily right at this moment, judging by the sizes of data sets and the complexity of analyses performed by CBS researchers. But things are changing, and if we look at the kinds of AI/ML computations that CBS and other social sciences/humanities universities are gradually moving into, the need will most probably arise in one-two years.
The most obvious example would be Deep Learning (needed for the training of LLMs (Large Language Models). Other examples could be the analysis of high-frequency financial data or computer vision/image identification (needed for predictive maintenance in an industry).
Read more:
Novo Nordisk Foundation, NVIDIA partner on AI research center
https://deic.dk/da/news/2024-4-10/deic-interactive-hpc-faar-nvidia-hopper-gpuer (in Danish only)
Questions? Please reach out to Lars Nondal