Machine learning

CSC's computing infrastructure supports a wide variety of tools for machine learning and deep learning. In particular, compute nodes with dedicated GPU accelerator cards (Pascal P100 and Volta V100) are available.

NEW! You might also be interested in our GPU-accelerated machine learning guide.


A variety of deep and machine learning frameworks can be used in the Puhti super cluster, in particular the Puhti-AI GPU partition. Note that, as with any other tasks, the Puhti login nodes are not intended for heavy computing. Please use batch jobs instead. In particular, the Puhti login nodes do not have any GPU cards installed.

Several machine learning-related GPU-optimized Python packages can be found pre-installed, including scikit-learn, TensorFlow, Keras, PyTorch, and MXNet are available via the module system.

GPU flavors at cPouta and ePouta

The cloud services cPouta and ePouta contain several types (flavors) of virtual machines, including GPU accelerated ones with 1–4 GPUs attached.  Virtual machines are particularly suited for cases with specific requirements for the operating system or software, or when administrative rights are needed.  GPU-enabled Docker containers can also be run in GPU-flavor instances in cPouta and ePouta.