# SLURM -- Training on the Artemis Cluster

The University of Sussex [Artemis HPC cluster](https://artemis-docs.hpc.sussex.ac.uk/artemis/) provides GPU nodes for large-scale training. Access requires VPN.

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# Single job

Submit one training run to SLURM:

``` bash
cellclass sbatch --args ~/data/mitosis-rpe/rois.npz \
    --model shufflenet2x1_0 --lr 1e-3 --lr-scheduler plateau \
    --flip 3 --batch-size 128 -d cuda --wandb
```

`cellclass sbatch` wraps `sbatch` and passes everything after `--args` to `cellclass train`. Use `cellclass sbatch --help` to see SLURM-specific options (partition, memory, walltime), or read them in the generated [`cellclass sbatch` reference](../reference/cli/sbatch.md).

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# Batch of SLURM jobs

Use the same `train.txt` batch file as for local training, but pass the SLURM submitter as the command:

``` bash
cellclass batch train.txt --script batch.sh --cmd "cellclass sbatch --args"
bash batch.sh
```

This generates one `sbatch` submission per line in `train.txt`. Each job runs independently on the cluster; results are logged to W&B as they complete.

**Important**: Comment out completed lines in `train.txt` before regenerating `batch.sh` to avoid resubmitting finished runs.

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# Weights & Biases on Artemis

Your W&B credentials stored in `~/.netrc` are available on Artemis if your home directory is mounted (it is by default). Verify before submitting jobs:

``` bash
wandb status
```

If credentials are missing, run `wandb login` from an Artemis login node.

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# Monitoring jobs

``` bash
squeue -u $USER          # List your queued/running jobs
scancel <job_id>         # Cancel a job
```

Training progress is also visible in real time on your W&B dashboard at <https://wandb.ai>.