Nebula Cloud Workbench for Deep Learning and AI

Nebula Cloud Workbench for Deep Learning and AI
30 December, 2022

Nebula Cloud Workbench for Deep Learning and AI

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What is Nebula Cloud Workbench for Deep Learning and AI?

The Nebula Cloud Workbench for Deep Learning and AI is your one-stop shop for deep learning and AI in the cloud. Deep Learning frameworks are pre-configured with latest versions of NVIDIA CUDA, cuDNN and Intel acceleration libraries such as MKL-DNN for high performance across CPU and GPU instance types.


Currently made available for Australia, India, Singapore, Europe (Stockholm, Frankfurt) and USA regions. Supported by AWS Cloud.

What do you get in Nebula Cloud Workbench?

Deep Learning Workbench on Nebula Cloud are built and optimized for building, training, debugging, and serving deep learning models in EC2 with popular frameworks such as TensorFlow, MXNet, PyTorch, and more. Deep learning frameworks are installed in Conda environments to provide a reliable and isolated environment for practitioners. Works only on GPU based virtual machines so please select the instance type accordingly.

Below are the core components of Deep Learning Virtual Machine:

·       Popular deep learning frameworks including TensorFlow (1.x, 2.x), PyTorch (1.x), and MXNet(1.x) performance tuned for using in Nebula Cloud. They are organized into Conda environments that are configured to be used out-of-the-box.

·       AWS Deep Learning Tools including AWS Elastic Fabric Adapter (EFA) and AWS Neuron.

·       NVIDIA Deep Learning Softwares Including NVIDIA GPU Driver, CUDA Toolkit, cuDNN, NCCL, and Fabric Manager.

·       Containerization platforms including Docker, and NVIDIA-Docker for build and run GPU accelerated Docker containers.

·       Intel Architecture performance library Intel MKL-DNN.

·       A collection of popular tools such as awscli, boto3, numpy, scikit-learn, opencv, pandas, matplotlib, graphviz, jupyter, ipython, and more.

In addition to the above popular frameworks, Nebula Cloud Workbench also provides prebuilt popular Deep Learning software and AI tools for research and development:

·       NVIDIA Instant Neural Graphics Primitives (NGP), a framework that allows a neural network to learn representations of gigapixel images, 3D objects, and NeRFs in seconds.

o   NeRFs use neural networks to represent and render realistic 3D scenes based on an input collection of 2D images. The images can automatically be sampled from a video or be a collection of videos.

o   Create 3D Scenes with Neural Networks.

·       Nerf Studio, A Complete package that allows for a simplified end-to-end process of creating, training, and visualizing NeRFs.

o   Create 3D Scenes with Neural Networks powered by NerF Studio

·       Stable Diffusion AI Version 2.1: Stable Diffusion creates images similar to Midjourney or OpenAI DALL-E. Supports text2image as well as img2img to create impressive images based on other images with a guidance prompt controlling the influence on the generated image.

·       Deforum Stable Diffusion: Create image sequences and videos automatically with Deforum Stable Diffusion.

·       NICE DCV, high-performance remote display protocol that provides customers with a secure way to deliver remote desktops and application streaming from any cloud or data centre to any device, over varying network conditions.

With NICE DCV and Nebula Cloud Workbench, customers can run graphics-intensive applications remotely on virtual workstation instances, and stream their user interface to simpler client machines, eliminating the need for expensive dedicated workstations. Customers across a broad range of HPC workloads use NICE DCV for their remote visualization requirements. Supports T4 GPUs with 16 GB of VRAM (g4dn family) and powerful A10 GPUs with 24 GB (g5 family) for large image rendering.

For the first time, Nebula Cloud has enabled all popular deep learning frameworks and AI software tools with the choice of GPU configurations and storage options (both SSD and HDD). It removes the burden on the content developers and business users for installation, configuration and administration of the software, algorithms, and models.

The platform significantly speeds-up the setup time and the use of software for various content development work in disciplines like Computer Vision, Deep Learning, Geospatial Intelligence, photogrammetry, 3D modelling, 3D rendering, Digital Twins and other industrial use cases.

Key Features of NVIDIA Instant NeRF on Nebula Cloud:
1.      Virtual Windows 10 Professional Workstation comes preconfigured with NVIDIA Instant NeRF with the choice of GPU (Tesla T4) and hardware configurations.

2.      Start using preconfigured Nebula Cloud Workbench in less than 5 minutes on Nebula Cloud.

3.      No hassles of installation, configuration and administration of the software and hardware.

4.      In-built data migration tool to move the data from on-premise IT systems to the cloud workstation and vice-versa.

5.      Scale-up/Scale-down the hardware and storage depending on the changes in the project and volume of the data.

6.      In-built SSD storage (Upto 5TB) for effecient data processing of imagery and videos.

7.      In-built HDD storage (Upto 5TB) for data storage and archival.

8.      Comes with NICE DCV, a high-performance remote display protocol that provides customers with a secure way to deliver remote desktops and application streaming from any cloud or data centre to any device, over varying network conditions.

9.      Comes preconfigured software and tools like WinSCP for FTP file transfer, Adobe Reader and many other.

10.  Pay only for the Cloud resources and used on Nebula Cloud.







Please note Nebula Cloud Workbench works only on GPU enabled virtual machines so you have to select the correct GPU instance type while creating the virtual machine. Please use g4dn.xlarge (4 Core, 16GB RAM, 1 GPU (16GB Memory) to start with or higher configuration as desired.


Nebula Cloud Workbench comes pre-configured and ready to use. You just have to start the session using the following commands:

·     Once the machine is deployed as per above recommendations, you will have a GPU enabled virtual machine created and ready for use.

You will see the login credentials once the machine comes into running state.

Use the login credentials provided and connect to the virtual machine via RDP i.e. Remote Desktop Connection.

·       Your Deep Learning and AI enabled Virtual Workstation is ready for use. You can prepare your data and run your models the way you want.


Sign-up for a free trial at and create your first 3D NeRF scene or
use stable diffusion generative AI art tools and showcase it to the world in minutes. 

For any support related queries and availability in your region, please write to or 

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