must.md

# Work on Annecy MUST center


General information:
- [Introduction au centre de calcul MUST](https://cta-lapp.pages.in2p3.fr/COURS/INTRODUCTION_MUST/)
- [MUST center documentation](https://doc.must-datacentre.fr/)

BEWARE:
- Due to lack of time, those configurations have been less tested than the others.
- The images below includes a copy of this repository which is obsolete, and also do not include the pedagogical material which comes from other repositories. Ignore the copy in the images and make fresh new clones of the required git repositories.


## Run SYCL with the MUST HTCondor job scheduler

Two light images have been prepared for the HTCondor job scheduler of the MUST center:
- [for CPU only](gitlab-registry.in2p3.fr/codeursintensifs/grayscott/grayscottsyclsetup/gray_scott_sycl_ubuntu_light) (2.43 GiB).
- [+ CUDA](gitlab-registry.in2p3.fr/codeursintensifs/grayscott/grayscottsyclsetup/gray_scott_sycl_ubuntu_cuda_light) (5.07 GiB).

Dedicated instructions are [here](https://gray-scott-lecture-demo-cta-lapp-cours-ab680a08433fbc37f8ada3ea.pages.in2p3.fr/3-313.html).


## Run SYCL on the MUST [Jupyter Kubernetes Cloud](https://jupyter.must-dc.cloud/)

Two images have been prepared for the JupyterHub of the MUST center (but not fully tested):
- [for CPU only)](gitlab-registry.in2p3.fr/codeursintensifs/grayscott/grayscottsyclsetup/gray_scott_sycl_ubuntu_micromamba_vscode) (2.99 GiB).
- [+ CUDA](gitlab-registry.in2p3.fr/codeursintensifs/grayscott/grayscottsyclsetup/gray_scott_sycl_ubuntu_cuda_micromama_vscode) (5.39 GiB).

Dedicated instructions are [here](https://gray-scott-lecture-demo-cta-lapp-cours-ab680a08433fbc37f8ada3ea.pages.in2p3.fr/4-478.html).


## Check SYCL

Once you have a Visual Studio Code Server running, a terminal, and a fresh clone of this repository, you can check the installation with commands similar to:

```sh
# move to the top directory
cd GrayScottSyclSetup/CheckOneApi

# check CPU nodes
sycl-ls
./intel.bash   # give the list of available devices
./intel.bash 1 # check the results of device 1

# Check GPU nodes
nvidia-smi
./cuda.bash   # give the list of available devices
./cuda.bash 4 # give the list of available devices
exit
```