1. login to prince (tutorial)

2. once your are in your home folder on prince clone this repo

   git clone [email protected]:JackLangerman/simpleprince.git

3. run setup.sbatch as a batch job from the simpleprince folder to setup and install miniconda and setup the ml environment. Feel free to add your favorite packages to environment.yml before running this step (you can do it later too).

   cd simpleprince
   sbatch setup.sbatch

to launch a jupyter notebook on prince (the ml environment exists):

On CPU (what you will want to use most of the time)

sbatch run-jupyter.sbatch 

on GPU (if you need it)

sbatch run-jupyterGPU.sbatch 

Also rembember you can use a jupyter notebook with GPU (or even TPU) for free at Google Colab

• to check the status of your job and where it is running

  squeue -u YOUR_NET_ID

• once you use squeue to check where your job is running you can get a terminal on that machine by SSHing into it ex:

  squeue -u YOUR_NET_ID
  
  JOBID PARTITION     NAME     USER ST	TIME  NODES NODELIST(REASON)
  15997001     p40_4    setup   jl4722  R	0:18	  1 gpu-52

  we see the job is running on gpu-52 so we can ssh in using

  ssh gpu-52

• once you ssh into the machine your job is running on you can monitor gpu status using watch nvidia-smi (exit by pressing cntrl-c)

• add new packages to your environment by putting them in your environment.yml file and then calling conda env update --prune from inside the simpleprince folder

• you can always access your ml environment on prince from any compute job by loading anaconda and then the environment

  module load tensorflow/python3.6/1.5.0
  module swap python3/intel  anaconda3/5.3.1
  source activate ml

• to check that GPUs are working in Jupyter:

  1. run a Jupyter GPU notebook after following steps above

  2. make a new terminal from Jupyter

     )

  3. run the test script

  python ~/simpleprince/testgpu.py

  OR from a standard terminal on prince:

  ssh gpu-##
  module load tensorflow/python3.6/1.5.0
  module swap python3/intel  anaconda3/5.3.1
  source activate ml