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Remote Rendering Server

Running Paraview Remote Rendering in Oscar

In order to follow this guide, you need access to Brown University's HPC system "Oscar". Please refer to the official ccv website and go to the Documentation section where you can find all the help related on how to connect and use it.

The Center for Computation and Visualization offers to the academic community a way to visualize datasets using Oscar and its powerful GPUs as a rendering server. The current hardware at the HPC surpass the common desktop models, offering a modern an robust solution to display large datasets in parallel jobs using the widely used opensource software Paraview. It is a simple "two steps" process. Start the server and connect the client.

Start the server

You need to allocate the resources via slurm indicating the amount of memory you want to reserve, plus a few optional parameters to configure your session. Luckily, there is a program in Oscar that facilitates this request.

First, load the paraview module that supports this service

module load paraview/5.9.0

and request resources to start the service as soon as they are available.

run-remote-server -u your_brown_username@brown.edu

By default, the script allocates 40G of RAM (320GB is the maximum at the moment). You can modify it by adding an extra parameter. The following is the description of the command plus the available configuration settings.

usage: run-remote-render [-n cores] [-t walltime] [-m memory] [-q queue] [-o outfile] [-g ngpus] [-u user brown email] Allocates resources, start up the render server and send and email to the user requesting the service options: -t walltime as hh:mm:ss (default: 1:30:00) -m memory as #[k|m|g] (default: 30G) -o outfile save a copy of the session's output to outfile (default: off) -q slurm partition (gpu (default)| gpu-he) -u brown email of the user requesting the service

In order to request a custom amount of memory add -m to the command.

run-remote-server -m 150G -u your_brown_email@brown.edu

By default, the nodes will be reserved in the gpu partition. However, this is the general slurm queue used by most of the projects running in Oscar. If you have access to a less busy slurm partition, you can point to it using the -q parameter.

run-remote-server -q <other-partition> -u your_brown_email@brown.edu

The only required parameter is -u <user-email>. The scripts uses it to email the specified account informing the service is ready to be used.

Queuing Times

The service depends on the availability of resources on the slurm partition. If you want to allocate a large amount of memory, expect high queuing times.

As the command executes as a batch job that will get resources when they are available, an email is sent to the user indicating that the service is running and the IP address you need to connect to.

Your PVSERVER connection is ready Your connection to paraview server is ready at: gpu1210.oscar.ccv.brown.edu:1111 The message indicates you have to connect to the server gpu1210.oscar.ccv.brown.edu through the port 11111 .

Connect to the server

Using your desktop computer (Recommended)

Go to the official Paraview Download website. Select your Operational system (Linux, Windows or Mac) and get the file ParaView-5.9.0-Windows-Python3 . Install in your environment, go to the installation directory and open Paraview.

Setting up Connection Tunneling.

If your local machine is not connected directly to the brown network, you have to follow this part. Open a terminal and execute the command:

ssh -N -L 11111:SERVER_IP:11111 your_brown_id@ssh.ccv.brown.edu

where SERVER_IP is the ip sent in the email and your_brown_id is your Brown username (It should be the same used to connect to the wi-fi) After typing your credentials, you will notice the terminal command line hangs. That is normal, it indicates you are connected and the tunneling is set up.

Connecting to the remote server

This step will reset the scene, so before doing it make sure to save all your data.

  1. In paraview UI go to menu bar File -> Connect ..

A. If you find a connection named Remote rendering. click ‘connect’

B. Otherwise go to ‘Add Server’:

name the connection ‘Remote Rendering’’, select Server type ‘Client / Server’,. The host is the IP sent in the email. In our example is localhost , and the port 11111

In the next screen, select Startup Type : Manual. Click on Save, select the new created connection and click ‘Connect’

After a few seconds, you get connected to the HPC automatically.

Using VNC Virtual Desktop

  1. Go to https://web1.ccv.brown.edu/technologies/vnc and download CCV VNC client 2.0.2

  2. Doble click on the CCV_VNC_2.0.1.jar

  1. Use your ccv user and password (usually are the same brown credentials)

  2. In the following pop up window select the last option ( 3 Cores - 15 GB Memory 2 GPU) and click on ‘Create VNC Session’’

Wait a few seconds (at least 60 seconds) to get the virtual desktop

Opening Paraview UI

  1. Open terminal: Applications - > Utilities -> Terminal (this might differ depending on the Operating System UI)

  2. Run the commands

$ module load paraview/5.9.0

$ paraview_ui

(it will take some minutes if it’s the first time opening paraview, don't despair)

After a while you’ll see on screen paraview ui:

Connecting to the remote server

This step will reset the scene, so before doing it make sure to save all your data.

  1. In paraview UI go to menu bar File -> Connect ..

  1. A. If you find a connection named Remote rendering. click ‘connect’

B. Otherwise go to ‘Add Server’:

name the connection ‘Remote Rendering’’, select Server type ‘Client / Server’,. The host is the IP sent in the email. In our example is gpu1210.oscar.ccv.brown.edu , and the port 11111

In the next screen, select Startup Type : Manual. Click on Save, select the new created connection and click ‘Connect’

After a few seconds, you get connected to the HPC automatically.

Verifying the connection is set up correctly.

In Paraview UI go to the menu bar "View" and select "Memory Inspector". You will notice a list of servers indicating the number of processes running on them

Summary

  1. Open a terminal an connect to Oscar (Follow this link to know how to do it)

  2. load the Paraview module module load paraview/5.9.0

  3. Execute the command run-remote-server -u your_brown_email@brown.edu.

  4. Wait for the email indicating the server is running

  5. Connect to the server using Paraview Client

If you find any issues following this guide or require additional help, do not hesitate contacting ccv services at support@ccv.brown.edu

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