Batch Visualization on Andes¶
It is best to work on andes.olcf.ornl.gov
. You will want to setup
a new env for andes. We’ll call it andes_env
.
You need to load python with anaconda support there:
module load python/3.7-anaconda3
then setup conda
:
conda init bash
this will modify your .bashrc, adding code that is specific to andes.
Then you do:
conda create -n andes_env -y ipykernel nb_conda_kernels
conda install -n andes_env -c conda-forge yt
Note
If you want to install yt from source, then you would first clone the yt repo:
git clone git@github.com:yt-project/yt
Then in the top-level yt/
directory, do:
pip install -e .
If you have an existing yt installation, you can uninstall it first via:
pip uninstall yt
Finally, you can activate the environment as:
source activate andes_env
Then you can run a python script that does visualization as with the following submission script:
#!/bin/bash
#SBATCH -A ast106
#SBATCH -J plots
#SBATCH -N 1
#SBATCH -t 2:00:00
cd $SLURM_SUBMIT_DIR
source activate andes_env
srun python vol-xrb-enuc.py flame_wave_1000Hz_25cm_smallplt203204
Here vol-xrb-enuc.py
is the script with the yt
code to make the visualization.
This is then submitted to SLURM via sbatch
.
Note
For very large plotfiles, it might run out of memory when doing the
visualization. A solution is to use the gpu
nodes on Andes,
which have more memory. This is accomplished by adding
#SBATCH -p gpu
to the script.