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2 changes: 1 addition & 1 deletion docs/platforms/mlp/index.md
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Expand Up @@ -17,7 +17,7 @@ The Machine Learning Platform (MLP) provides compute, storage and expertise to t
### Getting access

Project administrators (PIs and deputy PIs) of projects on the MLP can to invite users to join their project, before they can use the project's resources on Alps.
This is performed using the [project management tool][ref-account-waldur]
This is performed using the [project management tool][ref-account-waldur].

Once invited to a project, you will receive an email, which you need to create an account and configure [multi-factor authentication][ref-mfa] (MFA).

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4 changes: 2 additions & 2 deletions docs/software/sciapps/cp2k.md
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Expand Up @@ -66,7 +66,7 @@ On our systems, CP2K is built with the following dependencies:

## Running CP2K

### Running on the HPC platform
### Running on GH200 nodes
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We could call this Running on Daint as well? I left the heading further down as Running on Eiger, so it's a bit inconsistent like this. Open to better suggestions.

Motivation to change it: HPC platform includes both daint and eiger. Note to self, change the later mentions of "HPC platform" as well in this section...

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Running on Daint: CP2K is deployed on the HPC platform only, and users on that platform might be familiar with Daint, but not ght200.

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Maybe the first sentence could say something like: Daint nodes have 4 grace-hopper GPUs that have to be configured properly to get the best performance.?

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I agree, Running on Daint is both the most consistent option, and one that non-experts will understand.

As @bcumming suggests, it is probably a good idea to briefly remind users of the architecture of Daint (which was kinda self-contained in the GH200 title, but for expert users only)

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Thanks both for having a look. I've updated this to "Running on daint", and a few other places to match hopefully.


To start a job, two bash scripts are potentially required: a [Slurm] submission script, and a wrapper to start the [CUDA
MPS] daemon so that multiple MPI ranks can use the same GPU.
Expand Down Expand Up @@ -348,7 +348,7 @@ srun --cpu-bind=socket cp2k.psmp -i <CP2K_INPUT> -o <CP2K_OUTPUT>
for good performance. With [Intel MKL], this is not necessary and one can set `OMP_NUM_THREADS` to
`SLURM_CPUS_PER_TASK`.

* Change <ACCOUNT> to your project account name
* Change `<ACCOUNT>` to your project account name
* Change `<CP2K_UENV>` to the name (or path) of the actual CP2K uenv you want to use
* Change `<PATH_TO_CP2K_DATA_DIR>` to the actual path to the CP2K data directory
* Change `<CP2K_INPUT>` and `<CP2K_OUTPUT>` to the actual input and output files
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