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Usage policy

Login nodes

When you login to CSC supercomputers, you end up on one of the login nodes of the cluster. These login nodes are shared by all users and they are not intended for heavy computing.

The login nodes should be used only for:

  • compiling
  • managing batch jobs
  • moving data
  • light pre- and postprocessing

Here light means one-core jobs that finish in minutes and require less than 1 GiB of memory at maximum. All other tasks are to be done in compute nodes either as normal batch jobs or as interactive batch jobs. Programs not adhering to these rules will be terminated without warning.


The login nodes are not meant for long or heavy processes.

Disk cleaning

Each project has disk space in the directory /scratch/<project>. This fast parallel scratch space is intended for data that is in active use. To ensure that the parallel disk system does not run out of storage space and to keep performance acceptable CSC automatically removes files in scratch that have not been accessed in a long time. The performance of a parallel file system starts to degrade when it fills up, and the more it fills up, the slower the performance will get.

The current policy in Puhti is that files that have not been accessed for 12 months or more will be removed. This cleaning will happen regularly, and each time users are informed at least 1 month in advance. CSC also provides lists of files that are about to be removed and instructions for how one can transfer important files to more suitable disk systems.

A similar procedure will be introduced on Mahti, but it is not yet in place. The policy is still that users should keep only actively used data in scratch.

GPU nodes

Puhti and Mahti GPUs should only be used for workloads that greatly benefit from GPU capacity compared to using CPUs or which can't be run on CPUs. In particular AI/ML workloads are prioritized, since many of them cannot be done at all on CPUs. A good rule of thumb is to compare the billing unit (BU) usage (e.g. with seff or the billing unit calculator) of the job on GPUs against CPUs and select the one using less.

For Puhti and Mahti, this means that a full node of CPU cores roughly equals one GPU. However, since Puhti and Mahti have more CPU capacity than GPU, you might get access to CPUs with less queuing. Note that LUMI has a lot of GPU capacity which is also "cheaper" as measured in BUs, and on LUMI it's better to use GPUs if possible for your research. In any case, always make sure you use resources efficiently.

Conda installations

Due to performance issues of Conda-based environments on parallel file systems, CSC has deprecated the direct usage of Conda installations. This means that any Conda environments you intend to use must be installed within a container. See the page Deprecating Conda for more information.


Please consider the Tykky container wrapper for easy containerization of Conda and pip environments.

Last update: November 11, 2022