Rendering on HPC using multi-process

For a basic use (one node with OpenMP), the installation process of Blender on HPC is the same as on a local Linux computer. But you need to load the required modules when running. Blender needs OpenGL library. In a high-performance computing center, there are usually a couple of packages/libraries available. These include Mesa (open-source implementation of OpenGL) and also libGLU for GPU.

Use batoms

Save the following code as a python file (eg. h2o.py):

from ase.build import molecule
from batoms import Batoms
atoms = molecule('H2O')
h2o = Batoms(label = 'h2o', from_ase = atoms)
h2o.get_image([1, 0 ,0], engine = 'cycles', output = 'h2o.png')

Set up a job script on HPC, and save it (eg. job.slurm). Here is an example of the SLURM system on the Ubelix cluster at the University of Bern.

#!/bin/bash
#SBATCH --job-name=batoms
#SBATCH --output=test.out
#SBATCH --error=test.err
#SBATCH --time=00:20:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=20
#SBATCH --partition=epyc2
#SBATCH --mem-per-cpu=5GB

module load Mesa/.20.2.1-GCCcore-10.2.0

blender -b -P h2o.py > h2o.dat

And then submit the job.

submit job.slurm

Use blend file

Create your model locally, and save the file to myfile.blend.

#!/bin/bash
#SBATCH --job-name=batoms
#SBATCH --output=test.out
#SBATCH --error=test.err
#SBATCH --time=00:20:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=20
#SBATCH --partition=epyc2
#SBATCH --mem-per-cpu=5GB

module load Mesa/.20.2.1-GCCcore-10.2.0

blender -b myfile.blend -a

This will render an animation of the file myfile.blend with the settings with which the file was saved.

Performance

Here is a test for a system with 63 atoms. The performance is shown below. The speed scales well with the number of CPUs.

Number of CPU	Times (s)
2	97
4	40
8	25
16	13
32	11
64	8

Note

Blender does not support headless rendering using EEVEE. So please use CYCLES engine.

For multi-nodes, you have to build Blender manually. Suggest using the EasyBuild recipes.