---
title: Paraview
---
[toc]
## Environment Settings{#enviroment}
### Software Version and System Requirements{#version}
The Paraviews shown in the table below are available.
|Version | Module File Name | System A |System B/C | System G | Cloud System | Note
|--- | --- | --- | --- | --- | --- | ---
|1.1.2 | paraview/5.11.0 | + | + | + | + |
\+ ： Available for all users
\- ： Not available
## Software Overview {#overview}
Paraview is an open source software that allows users to analyze and visualize data.
It can read a wide variety of data formats, and by using the server/client method, it can also process large data sets.
## How to Use{#usage}
### Setting Up Environment (Executing the module Command)
Set up the environment by executing the `module` command. (Load the version of the module file which you want to use.)
```nohighlight
$ module load paraview
```
### How to Start (stand-alone method) {#run_standalone}
Execute the following command to start Paraview. Please refer to Interactive Processing (/run/interactive) for details on the tssrun command.
```nohighlight
$ tssrun -p gr19999b --x11 paraview
## The part *gr19999b* in the example must be changed to your own queue name.
## If you are not a personal or group course user, please enter "eb".
```
#### Use of threaded parallel computing {#openmp}
If you want to start Paraview using multiple cores or threads, you can use the --rsc
option to specify the number of cores to be used and number of threads in parallel.
```nohighlight
## Example: When starting with 4 cores and 4 threads
$ tssrun -p gr19999b --rsc c=4:t=4 --x11 paraview
## The part *gr19999b* in the example must be changed to your own queue name.
## If you are not a personal or group course user, please enter "eb".
```
### How to Start (server-client method) {#run_server_client}
ParavView's server-client mode can reduce the time required to analyze / visualize large data sets and expands the amount of data that can be analyzed / visualized at one time.
1. Execute the following command to start Paraview's server function.
```nohighlight
## 4 processes in MPI parallel, 10 cores per process and 4 threads allocated
$ tssrun -p gr19999b --rsc p=4:c=10:t=10 pvserver --force-offscreen-rendering
## The part *gr19999b* in the example must be changed to your own queue name.
## If you are not a personal or group course user, please enter "eb".
```
If the server function starts without problems, the console outputs the followings.
```nohighlight
Waiting for client...
Connection URL: cs://xb9999:11111
Accepting connection(s): xb9999:11111
```
The `Connection URL: cs://xb9999:11111` displayed is the host name and port information where the Paraview server function is running.
Please keep this information as it will be used in Section 5.
2. Launch a new console and start Paraview's client functions.
```nohighlight
## Example: Starting with 4 cores and 4 threads
$ tssrun -p gr19999b --rsc c=4:t=4 --x11 paraview
## The part *gr19999b* in the example must be changed to your own queue name.
## If you are not a personal or group course user, please enter "eb".
```
3. Once ParaView is started, press the area circled in blue and display the Window for connecting to the server.
4. The administration screen of the server to be connected will be displayed, press the area circled in red.
5. The new setup screen of the server will be displayed.In the text box labeled Host,
if the information displayed in Section 1. is **cs://xb9999:11111**, enter `xb9999-ib0` ( **hostname** + **-ib0**) .
In the text box labeled Port, if the information displayed in Section 1. is **cs://xb9999:11111**, enter `11111` (standby port number).
After completing the input, click the button marked "Configure" (circled in red).
6. When the client is started, a screen for selecting whether or not to automatically connect to the server is displayed.
Select "Manual (default)" for "Startup Type" and click the button marked "Save" (circled in red).
7. When you return to the server selection screen, make sure that the server set in Section 5 is selected, and click on "Connect" (circled in red).
With the above steps, some of the analysis/visualization processes will be available using a server launched with MPI parallelism.