1a. Quick Start (submit from a DoC Lab PC)
Open a Terminal window (Ubuntu/macOS, Windows 10 use Powershell built-in ssh and execute the following commands:
ssh gpucluster2.doc.ic.ac.uk
# or ssh gpucluster3.doc.ic.ac.uk
sbatch /vol/bitbucket/shared/slurmseg.sh
In this example, a user first logs into a Slurm submission host server (gpucluster2.doc.ic.ac.uk via ssh) and then submits a pre-existing script using the sbatch command. The output will be stored, by default, in the root of your '~/' home directory, with the filename slurm20-{xyz}.out.
If you have a bash script ready, replace '/vol/bitbucket/shared/slurmseg.sh' with the full path to your own script
Follow the next steps to learn how to prepare your own scripts for submission.
Example output of slurm20-xyz.out:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.129.06 Driver Version: 470.129.06 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA A30 On | 00000000:02:00.0 Off | 0 |
| N/A 32C P0 30W / 165W | 0MiB / 24258MiB | 0% Default |
| | | Disabled |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Follow the next steps to learn how to prepare your own scripts for submission, including building a python virtual environment and calling CUDA versions.