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Visualization

ParaView

-- currently under construction--

ParaView is an open-source, multi-platform data analysis and visualization application. The ParaView package comprises different tools which are designed to meet interactive, batch and in-situ workflows.

ParaView is available on ZIH systems from the modules system. The following command lists the available versions

marie@login$ module avail ParaView

   ParaView/5.4.1-foss-2018b-mpi  (D)    ParaView/5.5.2-intel-2018a-mpi                ParaView/5.7.0-osmesa
   ParaView/5.4.1-intel-2018a-mpi        ParaView/5.6.2-foss-2019b-Python-3.7.4-mpi    ParaView/5.7.0
[...]

Batch Mode - PvBatch

ParaView can run in batch mode, i.e., without opening the ParaView GUI, executing a Python script. This way, common visualization tasks can be automated. There are two Python interfaces: PvPython and PvBatch. The interface PvBatch only accepts commands from input scripts, and it will run in parallel, if it was built using MPI.

Note

ParaView is shipped with a prebuild MPI library and pvbatch has to be invoked using this very mpiexec command. Make sure to not use srun or mpiexec from another MPI module, e.g., check what mpiexec is in the path:

marie@login$ module load ParaView/5.7.0-osmesa
marie@login$ which mpiexec
/sw/installed/ParaView/5.7.0-osmesa/bin/mpiexec

The resources for the MPI processes have to be allocated via the batch system option --cpus-per-task=<NUM> (not --ntasks=<NUM>, as it would be usual for MPI processes). It might be valuable in terms of runtime to bind/pin the MPI processes to hardware. A convenient option is -bind-to core. All other options can be obtained by

marie@login$ mpiexec -bind-to -help

or from mpich wiki.

In the following, we provide two examples on how to use pvbatch from within a job file and an interactive allocation.

Example job file
#!/bin/bash

#SBATCH --nodes=1
#SBATCH --cpus-per-task=12
#SBATCH --time=01:00:00

# Make sure to only use ParaView
module purge
module load ParaView/5.7.0-osmesa

pvbatch --mpi --force-offscreen-rendering pvbatch-script.py
Example of interactive allocation using salloc
marie@login$ salloc --nodes=1 --cpus-per-task=16 --time=01:00:00 bash
salloc: Pending job allocation 336202
salloc: job 336202 queued and waiting for resources
salloc: job 336202 has been allocated resources
salloc: Granted job allocation 336202
salloc: Waiting for resource configuration
salloc: Nodes taurusi6605 are ready for job

# Make sure to only use ParaView
marie@compute$ module purge
marie@compute$ module load ParaView/5.7.0-osmesa

# Go to working directory, e.g., workspace
marie@compute$ cd /path/to/workspace

# Execute pvbatch using 16 MPI processes in parallel on allocated resources
marie@compute$ pvbatch --mpi --force-offscreen-rendering pvbatch-script.py

Using GPUs

ParaView Pvbatch can render offscreen through the Native Platform Interface (EGL) on the graphics cards (GPUs) specified by the device index. For that, make sure to use the modules indexed with -egl, e.g., ParaView/5.9.0-RC1-egl-mpi-Python-3.8, and pass the option --egl-device-index=$CUDA_VISIBLE_DEVICES.

Example job file
#!/bin/bash

#SBATCH --nodes=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:1
#SBATCH --time=01:00:00

# Make sure to only use ParaView
module purge
module load ParaView/5.9.0-RC1-egl-mpi-Python-3.8

mpiexec -n $SLURM_CPUS_PER_TASK -bind-to core pvbatch --mpi --egl-device-index=$CUDA_VISIBLE_DEVICES --force-offscreen-rendering pvbatch-script.py
#or
pvbatch --mpi --egl-device-index=$CUDA_VISIBLE_DEVICES --force-offscreen-rendering pvbatch-script.py

Interactive Mode

There are three different ways of using ParaView interactively on ZIH systems:

  • GUI via NICE DCV on a GPU node
  • Client-/Server mode with MPI-parallel off-screen-rendering
  • GUI via X forwarding

Using the GUI via NICE DCV on a GPU Node

This option provides hardware accelerated OpenGL and might provide the best performance and smooth handling. First, you need to open a DCV session, so please follow the instructions under virtual desktops. Start a terminal (right-click on desktop -> Terminal) in your virtual desktop session, then load the ParaView module as usual and start the GUI:

marie@dcv$ module load ParaView/5.7.0
marie@dcv$ paraview

Since your DCV session already runs inside a job, which has been scheduled to a compute node, no srun command is necessary here.

Using Client-/Server Mode with MPI-parallel Offscreen-Rendering

ParaView has a built-in client-server architecture, where you run the GUI locally on your desktop and connect to a ParaView server instance (so-called pvserver) on a cluster. The pvserver performs the computationally intensive rendering. Note that your client must be of the same version as the server.

The pvserver can be run in parallel using MPI, but it will only do CPU rendering via MESA. For this, you need to load the osmesa-suffixed version of the ParaView modules, which supports offscreen-rendering. Then, start the pvserver via srun in parallel using multiple MPI processes.

Example
marie@login$ module ParaView/5.7.0-osmesa
marie@login$ srun --nodes=1 --ntasks=8 --mem-per-cpu=2500 --partition=interactive --pty pvserver --force-offscreen-rendering
srun: job 2744818 queued and waiting for resources
srun: job 2744818 has been allocated resources
Waiting for client...
Connection URL: cs://taurusi6612.taurus.hrsk.tu-dresden.de:11111
Accepting connection(s): taurusi6612.taurus.hrsk.tu-dresden.de:11111

If the default port 11111 is already in use, an alternative port can be specified via -sp=port. Once the resources are allocated, the pvserver is started in parallel and connection information are output.

This contains the node name which your job and server runs on. However, since the node names of the cluster are not present in the public domain name system (only cluster-internally), you cannot just use this line as-is for connection with your client. You first have to resolve the name to an IP address on ZIH systems: Suffix the node name with -mn to get the management network (ethernet) address, and pass it to a lookup-tool like host in another SSH session:

marie@login$ host taurusi6605-mn
taurusi6605-mn.taurus.hrsk.tu-dresden.de has address 172.24.140.229

The SSH tunnel has to be created from the user's localhost. The following example will create a forward SSH tunnel to localhost on port 22222 (or what ever port is preferred):

marie@local$ ssh -L 22222:172.24.140.229:11111 taurus

SSH command

The previous SSH command requires that you have already set up your SSH configuration.

The final step is to start ParaView locally on your own machine and add the connection

  • File -> Connect...
  • Add Server
    • Name: localhost tunnel
    • Server Type: Client / Server
    • Host: localhost
    • Port: 22222
  • Configure
    • Startup Type: Manual
    • -> Save
  • -> Connect

A successful connection is displayed by a client connected message displayed on the pvserver process terminal, and within ParaView's Pipeline Browser (instead of it saying builtin). You now are connected to the pvserver running on a compute node at ZIH systems and can open files from its filesystems.

Caveats

Connecting to the compute nodes will only work when you are inside the TU Dresden campus network, because otherwise, the private networks 172.24.* will not be routed. That's why you either need to use VPN, or, when coming via the ZIH login gateway (login1.zih.tu-dresden.de), use an SSH tunnel. For the example IP address from above, this could look like the following:

marie@local$ ssh -f -N -L11111:172.24.140.229:11111 <zihlogin>@login1.zih.tu-dresden.de

This command opens the port 11111 locally and tunnels it via login1 to the pvserver running on the compute node. Note that you then must instruct your local ParaView client to connect to host localhost instead. The recommendation, though, is to use VPN, which makes this extra step unnecessary.

Using the GUI via X-Forwarding

(not recommended)

Even the developers, KitWare, say that X-forwarding is not supported at all by ParaView, as it requires OpenGL extensions that are not supported by X forwarding. It might still be usable for very small examples, but the user experience will not be good. Also, you have to make sure your X-forwarding connection provides OpenGL rendering support. Furthermore, especially in newer versions of ParaView, you might have to set the environment variable MESA_GL_VERSION_OVERRIDE=3.2 to fool it into thinking your provided GL rendering version is higher than what it actually is.

Example

The following lines requires that you have already set up your SSH configuration.

# 1st, connect to ZIH systems using X forwarding (-X).
# It is a good idea to also enable compression for such connections (-C):
marie@local$ ssh -XC taurus

# 2nd, load the ParaView module and override the GL version (if necessary):
marie@login$ module Paraview/5.7.0
marie@login$ export MESA_GL_VERSION_OVERRIDE=3.2

# 3rd, start the ParaView GUI inside an interactive job. Don't forget the --x11 parameter for X forwarding:
marie@login$ srun --ntasks=1 --cpus-per-task=1 --partition=interactive --mem-per-cpu=2500 --pty --x11=first paraview