Machine learning

Our computing infrastructure supports a wide variety of tools for machine learning and deep learning. In particular, compute nodes with dedicated GPU accelerator cards (Volta V100 and Ampere A100) are available.

To learn more about machine learning using CSC's computing resources, take a look at the machine learning guide.

Puhti and Mahti supercomputers

A variety of deep and machine learning frameworks can be used on Puhti and Mahti supercomputers, in particular the GPU partitions. Note that, as with any other tasks, the login nodes are not intended for heavy computing. They do not have any GPU cards installed. Please use batch jobs instead.

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

GPU flavors on cPouta and ePouta

Our 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 to be run in GPU-flavor instances on cPouta and ePouta.