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Ubuntu 22 Remote Desktop with high-end NICE DCV Remote 3D experience - includes NVIDIA GPU 3D performance drivers and CUDA Toolkit. Llama.cpp inference and NVIDIA Docker support.
5
Overview
NICE DCV is a high performance remote streaming protocol that enables user to securely access remote desktop or application sessions, including 3D graphics applications hosted on servers with high-performance GPUs.
NICE DCV offers end users a wide range of client devices, including native clients for Windows, Linux, and MacOS operating systems. Native clients support up to 4 monitors at 4K resolution each and the Windows client also supports USB redirection for 3D mice and USB storage devices. The QUIC/UDP protocol is enabled as well for best interactive performance.
NICE DCV Ubuntu 22 Desktop supports high end remote 3D access for e.g. HPC or media pre-/post-processing applications. Includes support for remote USB devices and file transfer. NVIDIA drivers pre-installed for high-end remote 3D experience. On AWS, NICE DCV provides the streaming protocol e.g. used by Amazon Appstream 2.0, AWS RoboMaker and AWS Nimble Studio.
Latest version includes CUDA Toolkit 12.2 and nvcc. Includes NIVIDIA DOCKER Container support.
Latest version includes neural network inference support for quantized models via llama.cpp. See Usage Information for more background and https://www.ai-sp.com/how-to-run-a-70b-nn-model-on-a-standard-server/ . g4dn and g5 instances supported for inference.
This AMI with Ubuntu 22 supports g5, g4dn, g3 and p3 (V100) instance families.
Highlights
- Remote Performance: Responsive and secure streaming experience allowing customers to run graphics intensive applications remotely removing the need for expensive dedicated workstations or transferring large amounts of data. Based on NICE DCV from AWS.
- Secure TLS encrypted high-end 3D remote desktop connection on powerful NVIDIA based cloud GPUs. Includes remote USB support and file transfer.
- Ubuntu 22 desktop with full superuser access to add and manage own applications. Leverages high NVIDIA GPU cloud GPUs.
Details
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
g4dn.2xlarge Recommended | $0.04 |
g4dn.metal | $0.48 |
p3.8xlarge | $1.20 |
p3.16xlarge | $2.40 |
g5.2xlarge | $0.12 |
g6.2xlarge | $0.12 |
g5.4xlarge | $0.16 |
g6.4xlarge | $0.15 |
g4dn.xlarge | $0.03 |
g4dn.12xlarge | $0.32 |
Dimensions summary
You pay by the hour for a preconfigured Ubuntu 22 remote desktop with GPU 3D and CUDA support. Billing is usage-based, so you are charged only for the hours each instance runs. Each dimension maps to a specific NVIDIA-GPU EC2 instance type across the g4dn, g5, g6, g6e, g7e, and p3 families. Larger instance sizes within a family carry more GPU, CPU, and memory resources, so hourly rates scale with the size you pick. You choose the instance that fits your workload, and cost tracks the running hours of your selection.
Top-of-mind questions for buyers
Each hourly rate covers a preconfigured Ubuntu 22 remote desktop running on one matching NVIDIA-GPU EC2 instance, with 3D graphics and CUDA drivers installed. You pay for each hour the instance runs. Larger sizes in a family include more GPU, CPU, and memory, so their hourly rate is higher.
Software charges meter running hours only, so a stopped instance stops accruing the hourly software fee. Underlying AWS storage for the stopped instance may still apply through your AWS account. To halt software billing, stop the instance rather than leaving it idle but running.
Yes. On Linux, the software supports GPU sharing, letting multiple users run separate high-performance 3D desktops on one physical server that shares GPU, CPU, and memory. This does not change billing. You still pay the single hourly rate for that one running instance.
www.ni-sp.com
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No refund
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Includes NICE DCV 2025.0-20103. More information can be found here: https://www.ni-sp.com/dcv-now-supports-amazon-ec2-mac-instances/ . Security fixes. Updated Ubuntu 22.04. Supports g7e instances. Newest NVIDIA driver.
Additional details
Usage instructions
Make sure the instance security groups allow inbound traffic to TCP and UDP port 8443 and 22.
To connect you have different options:
Option 1: Connect with the native NICE DCV Client for best performance
- Download the NICE DCV client from: https://download.nice-dcv.com/ (includes Windows portable client)
- In the DCV client connection field enter the instance public IP to connect.
- Sign in using the following credentials: User: ubuntu. Password: last 6 digits of the instance ID.
Option 2: Connect with NICE DCV Web Client for convenience
- Connect with the following URL: https://IP_OR_FQDN:8443/, e.g. https://3.70.184.235:8443/
- Sign in using the following credentials: User: ubuntu. Password: last 6 digits of the instance ID.
Option 3: Set your own password and connect
- Connect to your remote machine with ssh -i <your-pem-key> ubuntu@<public-dns>
- Set the password for the user "ubuntu" with sudo passwd ubuntu. This is the password you will use to log in to DCV
- Connect to your remote machine with the NICE DCV native client or web client as described above
- Enter your credentials and you are ready to rock
With DCV QUIC/UDP will be used automatically together with the DCV native client. In the DCV client connection settings you can select TCP as well. Please do not perform an update to a new kernel or higher releases as it might disable the GPU driver.
In case of interest in Inferencing with llama.cpp we have created a dedicated Inference server: https://aws.amazon.com/marketplace/pp/prodview-y3u47mo7fsbdm
Resources
Support
Vendor support
Technical documentation (https://aws.amazon.com/documentation/dcv/ ) and NI SP Tips and Tricks (https://www.ni-sp.com/nice-dcv-tips-and-tricks/ ). Free support is available through forums (https://forums.aws.amazon.com/forum.jspa?forumID=366 )
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By NI SP - High-End Remote Desktop and HPC
By Arara Solutions
By netCUBED
AI generated from product descriptions
Remote 3D Graphics Streaming
NICE DCV high-performance remote streaming protocol enabling secure access to 3D graphics applications on GPU-accelerated servers with support for up to 4 monitors at 4K resolution each
GPU Compute Toolkit
CUDA Toolkit 12.2 with nvcc compiler pre-installed for GPU-accelerated computing and development on NVIDIA GPUs
Neural Network Inference
Llama.cpp support for quantized neural network model inference on g4dn and g5 instances
Container Virtualization
NVIDIA Docker container support for containerized GPU-accelerated applications
Remote Device Access
USB redirection capability for 3D mice and USB storage devices with remote file transfer support over QUIC/UDP protocol
Remote Desktop Protocol
NICE DCV for remote access with high-performance remote desktop and application streaming capabilities
Security Protocol
TLS protocol encryption for securing both pixels and end-user inputs in remote sessions
Desktop Environment
Gnome graphical user interface configured for remote access
Operating System
Ubuntu 22.04 LTS as the base operating system
Network Optimization
Optimized for remote access over the Internet with efficient data transmission
Browser-Based Access
Jupyter notebooks, RStudio Server, Terminal sessions, and Remote Desktop accessible through web interface without requiring client software installation
Remote Desktop Protocol Support
Native Remote Desktop client connectivity enabling access to full Ubuntu 24.04 Desktop environment with copy-paste and drag-and-drop file upload capabilities
HTTPS Encryption
All web endpoints proxied through HTTPS with strong encryption for secure data transmission
Pre-installed Development Tools
Includes Google Chrome, Visual Studio Code, Docker, and other development utilities for software development and data science workflows
Standard contract
No
Customer reviews
Neil
working well
Reviewed on Aug 02, 2022
Review from a verified AWS customer
This AMI is working well for CUDA computing + NVIDIA graphics + NICE DCV remote interactive visualization on P and G instances