From 0f1dea57788e4d5adf491e29f4c52afd7f035fe2 Mon Sep 17 00:00:00 2001
From: Adam Tyson <code@adamltyson.com>
Date: Fri, 24 Nov 2023 13:10:47 +0000
Subject: [PATCH] Remove readme

---
 demo/README.md | 153 -------------------------------------------------
 1 file changed, 153 deletions(-)
 delete mode 100644 demo/README.md

diff --git a/demo/README.md b/demo/README.md
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-## SWC SLURM demo
-
-1. Login to gateway
-
-```bash
-ssh USERNAME@ssh.swc.ucl.ac.uk
-```
-
-2. Login to HPC
-
-```
-ssh hpc-gw1
-```
-
-N.B. You can [set up SSH keys](https://www.digitalocean.com/community/tutorials/how-to-set-up-ssh-keys-2) so you don't have to keep typing in your password.
-
-3. See what nodes are available using `sinfo`.
-
-N.B. Adding this line to your `.bashrc` and typing `sinfol` will print much more information.
-```bash
-alias sinfol='sinfo --Node --format="%.14N %.4D %5P %.6T %.4c %.10C %4O %8e %.8z %.6m %.8d %.6w %.5f %.6E %.30G"'
-```
-3. See what jobs are running with `squeue`.
-
-4. See what data storage is available:
-* `cd /ceph/store`  - general lab data storage
-* `cd /nfs/winstor` - older lab data
-* `/ceph/neuroinformatics/neuroinformatics` - team storage
-* `cd /ceph/zoo` - specific project storage
-* `cd /ceph/scratch` - short term storage, e.g. for intermediate analysis results, not backed up
-* `cd /ceph/scratch/neuroinformatics-dropoff` - "dropbox" for others to share data with the team
-
-5. Start an interactive job in pseudoterminal mode (`--pty`) by requesting a single core from [SLURM](https://slurm.schedmd.com/documentation.html), the job scheduler:
-
-```bash
-srun -p cpu --pty bash -i
-```
-N.B. Don't run anything intensive on the login nodes.
-
-6. Clone a test script
-```bash
-cd ~/
-git clone https://github.com/neuroinformatics-unit/slurm-demo
-```
-7. Check out list of available modules
-```bash
-module avail
-```
-8. Load the miniconda module
-```bash
-module load miniconda
-```
-
-9. Create conda environment
-```bash
-conda env create -f env.yml
-```
-
-10. Activate conda environment and run Python script
-```bash
-conda activate slurm_demo
-python python multiply.py 5 10 --jazzy
-```
-11. Stop interactive job
-```bash
-exit
-```
-12. Check out batch script:
-```bash
-cat batch_example.sh
-```
-
-```bash
-#!/bin/bash
-
-#SBATCH -p gpu # partition (queue)
-#SBATCH -N 1   # number of nodes
-#SBATCH --mem 2G # memory pool for all cores
-#SBATCH -n 2 # number of cores
-#SBATCH -t 0-0:10 # time (D-HH:MM)
-#SBATCH -o slurm_output.out
-#SBATCH -e slurm_error.err
-#SBATCH --mail-type=ALL
-#SBATCH --mail-user=adam.tyson@ucl.ac.uk
-
-module load miniconda
-conda activate slurm_demo
-
-for i in {1..5}
-do
-  echo "Multiplying $i by 10"
-  python multiply.py $i 10 --jazzy
-done
-```
-Run batch job:
-```bash
-sbatch batch_example.sh
-```
-
-13. Check out array script:
-```bash
-cat array_example.sh
-```
-
-```bash
-#!/bin/bash
-
-#SBATCH -p gpu # partition (queue)
-#SBATCH -N 1   # number of nodes
-#SBATCH --mem 2G # memory pool for all cores
-#SBATCH -n 2 # number of cores
-#SBATCH -t 0-0:10 # time (D-HH:MM)
-#SBATCH -o slurm_array_%A-%a.out
-#SBATCH -e slurm_array_%A-%a.err
-#SBATCH --mail-type=ALL
-#SBATCH --mail-user=adam.tyson@ucl.ac.uk
-#SBATCH --array=0-9%4
-
-# Array job runs 10 separate jobs, but not more than four at a time.
-# This is flexible and the array ID ($SLURM_ARRAY_TASK_ID) can be used in any way.
-
-module load miniconda
-conda activate slurm_demo
-
-echo "Multiplying $SLURM_ARRAY_TASK_ID by 10"
-python multiply.py $SLURM_ARRAY_TASK_ID 10 --jazzy
-```
-Run array job:
-```bash
-sbatch array_example.sh
-```
-
-14. Start an interactive job with one GPU:
-```bash
-srun -p gpu --gres=gpu:1 --pty bash -i
-```
-
-14. Load CUDA
-```bash
-module load cuda
-```
-15. Activate conda environment check GPU 
-```bash
-conda activate slurm_demo
-python
-```
-
-```python
-import tensorflow as tf
-tf.config.list_physical_devices('GPU')
-```
-
-16. For fast I/O consider copying data to `/tmp` (fast NVME storage) as part of the run. Available on all of the gpu-380 and gpu-sr670 nodes.