Skip to content

Latest commit

 

History

History
69 lines (46 loc) · 3.64 KB

aws-ami-paraview.md

File metadata and controls

69 lines (46 loc) · 3.64 KB

Single instance rendering using IndeX for ParaView plugin

Launch an EC2 instance with the NVIDIA IndeX AMI:

  • Go to the NVIDIA IndeX offering in the AWS Marketplace and subscribe to the image.

  • To launch an instance, please use the following CloudFormation template form. Alternatively, you can also use the aws cli tool to launch the CloudFormation template:

    

    • 



aws cloudformation deploy --stack-name single-instance-index-cfn --template-file resources/index-single-ami-cloud-formation-template.yaml --parameter-overrides 'KeyName=' --capabilities CAPABILITY_IAM



- You can launch any type of Amazon EC2 GPU instances (G4 or P3) based on your dataset requirements.
- For this example launch a *p3.8xlarge* instance (which has 4 NVIDIA V100s, total of 64GB of GPU memory) using the custom AMI.
- Please remember your selected NICE DCV password for the step below.

## Configure Security groups on your EC2 instance

- By default, the NICE DCV server is configured to communicate over port 8443.

- During the "Configure Security Group" of instance launch, add `Custom TCP` and enter Port `8443` in inbound rules of the security group for the instance. You might want to add the SSH port as well at this stage.

## Connect to the instance using the DCV Client or Web-browser:

- Note: You can download the NICE DCV Client from [here](https://download.nice-dcv.com/)
- OR Open your preferred web browser and enter the NICE DCV server URL in the following format `https://<server_public-ip>:8443`
- To log in, enter `ubuntu` as username and the password selected in the CloudFormation template (default value: `IndeXonAW$`).

## Download and Start ParaView

- Run the utility script to install ParaView with NVIDIA IndeX enabled:
```sh
/opt/scripts/install-paraview.sh



    

  • Start ParaView:
    • 



ParaView-5.8.1-MPI-Linux-Python3.7-64bit/bin/paraview


Opening the sample dataset


    

  • Fetch the sample supernova dataset:
    • 



cd ~/Downloads
wget https://nvindex-datasets-us-west2.s3-us-west-2.amazonaws.com/scenes/00-supernova_ncsa_small/data/Export_entropy_633x633x633_uint8_T1074.raw 


    

  • 

    Click on File → Open → <path-to> → Export_entropy_633x633x633_uint8_T1074.raw
    

      

    • Click OK
      • 

    • Open Data with Image Reader
      • 

    

    • 

  • 

    Update the properties for this data set.
    

      

    • The data set used here is unsigned char data type
      • 

    • Confirm the Data Byte Order for your system (LittleEndian vs. BigEndian). You can use this to find out. For example, on a x86 system you would select Little Endian.
      • 

    • Data Extent is the X, Y, Z dimension of the dataset (its specified in the name of file). For this dataset it would be [0, 632] for X, Y and Z dimensions.
      • 

    

    • 

  • 

    Change colouring from SolidColor to ImageFile.
    

    • 

  • 

    Change representation to use the NVIDIA Index renderer: Click on the Outline dropdown and select NVIDIA IndeX.
    

    • 

  • 

    At this point you should see a colured cube. Change the data range (via colormap or Rescale to Data Range button) to  to [25, 255].
    

    • 

  • 

    At this point you should see the features of the dataset. Feel free to use the colormap to highlight different features.
    

    • 

  • 

    Here's a sample rendering screenshot:

    

    • 

  • 

    The dataset shown here is a time step in a core-collapse supernovae simulation. Credits
    

    •