In the previous section we ran OpenFOAM simulation in a batch mode using the cluster SLURM scheduler. Given the command-line nature of OpenFOAM this is normally sufficient. However a key requirement for a typical OpenFOAM user is to use Paraview to visualize the solution and/or mesh. The lack of a GPU on the headnode and the limited amount of RAM and vCPUs mean it’s not suitable for this pre and post-processing.
For this situation it is best to use the GPU visualization node we created in Section 4.
The first step is for us to upload Paraview to S3. For this workshop the easiest way is to download the Paraview binary and simply untar it and use directly without compilation. For those who want to compile it themselves please follow the instructions on the Paraview website.
Head to https://www.paraview.org/download/ and download the Linux version of the following package:
You can then follow the steps in Section (create a S3 bucket) to upload to your S3 bucket.
In this example we picked the G4dn.4xlarge which has 16vCPU and 64GB RAM, however we could have picked the g4dn.16xlarge which has 64vCPU and 256GB RAM (and there are instances with even higher number of cores and RAM).
To illustrate this, connect to the GPU node using the the NICE DCV client application as described in Section 4. Which means go to the EC2 console to note the public IP address and enter this as the IP to connect to. Next enter the username (ec2-user) and password.
You can then open up the terminal application as shown below:
Once you’re here, you can download Paraview from your S3 bucket:
Next lets copy from S3 the Paraview files that you’ve uploaded.
aws s3 cp s3://yourbucketname/ParaView-5.8.1-MPI-Linux-Python2.7-64bit.tar.gz .
Lets untar it:
tar -xf ParaView-5.8.1-MPI-Linux-Python2.7-64bit.tar.gz
You can then head to the folder and just run Paraview straight from the folder:
You can then open up the file that was run in the previous section as shown below.
If you are loading up the slice shown in this example, select the ‘+Y’ option to change the view and then you can pick a scalar to view e.g U velocity from the top bar.
You can then close it down and then follow instructions in Section 4 to clean up your environment if you’re finished.
This was just a basic example of OpenFOAM but hopefully it gives you an example of how it can be used on AWS.