# Running on a SLURM cluster

`bin/sbatch_omero_screen.py` writes a SLURM job script that runs `omero-screen` and submits it with `sbatch`. It is set up for the Sussex HPC (job classes, GPU nodes); other clusters will need its template adjusted.

> **Note: Note**
>
> This is a `bin/` utility and still uses argparse, unlike the installed commands. It keeps argparse conventions, including abbreviated options.

``` bash
python bin/sbatch_omero_screen.py 12345 67890 --env production --stitch --track
```

By default it submits one job per plate ID.


# Job options

| Option | Default | Effect |
|----|----|----|
| `--class CLASS` | `gpu` | SLURM job class |
| `-u`, `--username USER` | current user | Cluster username |
| `-t`, `--threads N` | 1 | CPU threads; raise it when running without a GPU |
| `--hours N` | 24 | Wall-clock limit in hours |
| `-m`, `--memory N` | 32 | Memory in GB |
| `--gpu` / `--no-gpu` | on | Request a GPU node |
| `--exec` / `--no-exec` | on | Execute the generated script statements |
| `--submit` / `--no-submit` | on | Submit with `sbatch` |
| `--multi-submit` / `--no-multi-submit` | on | One job per plate ID |

The memory you request becomes the job's cgroup limit, which the pipeline reads to decide whether to [stream the stitch](stitching.md#host-memory).


# Pipeline options

These are forwarded to `omero-screen` in every job. They mean the same as in the [CLI reference](../reference/cli/omero_screen.md).

| Option | Forwarded as |
|----|----|
| `--env ENV` | `--env` |
| `--config PATH` | `--config`, resolved to an absolute path and checked at submission |
| `--inference MODEL [MODEL ...]` | `--inference` |
| `--segmentation` | `--segmentation` |
| `--delete` | `--delete` |
| `--cp4`, `--model MODEL` | `--cp4`, `--model` |
| `--stitch`, `--stitch-config PATH` | `--stitch`, `--stitch-config` |
| `--stream-stitch` / `--no-stream-stitch` | the same |
| `--track [MODEL]`, `--track-mode`, `--track-device`, `--track-window`, `--track-batch-size` | the same |