> For the complete documentation index, see [llms.txt](https://docs.aisl.science/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aisl.science/external-tools-and-services/cscs-clariden.md).

# CSCS Clariden

Quick start for accessing CSCS Clariden and validating SSH, Slurm, Python, GPU jobs, uenv, and the ML Console.

[Clariden](https://docs.cscs.ch/clusters/clariden/) is the CSCS machine-learning cluster on Alps. FHNW/AISL users can use it when access has been allocated through a course, research project, workshop, event, or other approved activity.

## JupyterHub / JupyterLab

For interactive teaching and notebook-based experimentation, use the [Clariden JupyterHub](https://jupyter-clariden.cscs.ch/).

After signing in, select the project/account, partition, wall time, and runtime environment provided for your course or project. A tested Apertus setup used:

* Partition: `Dedicated`
* Runtime image: `nvcr.io/nvidia/pytorch:25.04-py3`
* Advanced options: left empty
* Hardware exposed to the notebook: 4 x NVIDIA GH200 120 GB

For the complete notebook workflow, see [Training Apertus on CSCS Clariden](https://docs.aisl.science/learning-and-resources/training-apertus/cscs-clariden).

When finished, stop the Jupyter server through the Hub control panel. Logging out of JupyterLab alone does not necessarily terminate the underlying Slurm allocation.

## Before you start

You need a CSCS account with MFA, access to a project or course allocation that includes Clariden, and the corresponding Slurm project/account code.

Do not share private SSH keys, passwords, CSCS credentials, Hugging Face tokens, or other secrets.

## SSH and Slurm

SSH remains useful for batch jobs, command-line workflows, and debugging outside JupyterLab.

1. Confirm your allocation at [portal.cscs.ch](https://portal.cscs.ch/).
2. Create a local SSH key if needed.
3. Sign the public key at [user-account.cscs.ch](https://user-account.cscs.ch/).
4. Use the SSH configuration provided by CSCS.
5. Connect with `ssh cscs-clariden`.
6. Run compute workloads through Slurm, not directly on the login node.

A minimal allocation check is:

```bash
srun --account=<PROJECT> hostname
```

## CSCS ML Console

The [CSCS ML Console](https://console.mlp.cscs.ch/) is useful for monitoring jobs, viewing StdOut/StdErr, browsing accessible filesystems, and submitting simple jobs. It is a companion to JupyterHub, SSH, and Slurm rather than a separate compute system.

## Related resources

* [Training Apertus on CSCS Clariden](https://docs.aisl.science/learning-and-resources/training-apertus/cscs-clariden)
* [CSCS SSH documentation](https://docs.cscs.ch/access/ssh/)
* [Clariden documentation](https://docs.cscs.ch/clusters/clariden/)
* [CSCS JupyterLab documentation](https://docs.cscs.ch/software/jupyterlab/)
* [CSCS HPC Console documentation](https://docs.cscs.ch/access/hpc-console/)


---

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