Sold by: Intuz
Pre-configured AMI with Python, CUDA Toolkit, and JupyterLab for seamless development. Ideal for developers and data scientists who need a ready-to-use environment for GPU-accelerated workflows, machine learning, and data analysis without the hassle of manual setup.
Overview
This AWS AMI provides a fully-configured environment featuring Python, CUDA Toolkit, and JupyterLab, designed to streamline your development process. Whether you're building AI models, running machine learning experiments, or performing data analysis, this solution eliminates the hassle of manual setup. With GPU support powered by CUDA, your workflows are accelerated for faster results, allowing you to focus more on development and less on configuration.
Ideal for both experienced developers and data scientists, this AMI enables a smooth, out-of-the-box experience. No need to install or configure the CUDA drivers or libraries - everything is pre-installed and ready for use. Simply launch the instance, and you're set to start building and experimenting with your AI/ML models immediately. It's the perfect choice for anyone looking to quickly set up a high-performance development environment without the usual setup time.
Enjoy the benefits of an optimized, GPU-powered instance for high-performance computing tasks, saving you time and effort while ensuring you have all the essential tools for AI and ML development right at your fingertips.
Highlights
- Pre-configured for AI/ML: Launch a fully set up environment with Python, CUDA Toolkit, and JupyterLab - no manual configuration required.
- GPU-Accelerated Workflows: Leverage the power of CUDA for fast, efficient machine learning, data analysis, and AI model development.
- Seamless Development Experience: Start building right away with a hassle-free, optimized AWS instance tailored for high-performance computing tasks.
Details
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Typical total price
This estimate is based on use of the seller's recommended configuration (g4dn.xlarge) in the US East (N. Virginia) Region. View pricing details
$0.616/hour
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
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 covering 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.
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
p3.2xlarge | $0.09 | $3.06 | $3.15 |
p3.8xlarge | $0.09 | $12.24 | $12.33 |
p3.16xlarge | $0.09 | $24.48 | $24.57 |
p3dn.24xlarge | $0.09 | $31.212 | $31.302 |
g2.2xlarge | $0.09 | $0.65 | $0.74 |
g2.8xlarge | $0.09 | $2.60 | $2.69 |
g3.4xlarge | $0.09 | $1.14 | $1.23 |
g3.8xlarge | $0.09 | $2.28 | $2.37 |
g3.16xlarge | $0.09 | $4.56 | $4.65 |
g3s.xlarge | $0.09 | $0.75 | $0.84 |
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
Intuz will not refund money in any case.However, you can cancel your subscription any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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
Initial release of the AWS AMI pre-configured with Python, CUDA Toolkit, and JupyterLab. Optimized for AI/ML development and high-performance GPU-accelerated workflows. Includes all necessary drivers and libraries, eliminating the need for manual setup. Ready-to-use environment for quick deployment of machine learning and data science projects.
Additional details
Usage instructions
To get started, navigate to http://Instance-IP to check system and graphics card information. To access JupyterLab, go to http://Instance-IP/lab and use the Instance-ID as the default password. If you'd like to change the JupyterLab password, simply run the command bash /home/ubuntu/iscripts/jupyter_lab.sh in the terminal. This will update the password to your desired value for secure access.
Support
Vendor support
We provide best effort technical support for this product. We will do our best to respond to your questions within the next 24 hours in business days. For any technical support or query, you can drop an email here: cloudsupport@intuz.com or fill up this form:
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.
Similar products
NVIDIA CUDA Suit: Complete NVIDIA GPU Development Suit
By Techlatest.net
NVIDIA CUDA Suit VM Solution with support from Techlatest.net is the ultimate platform for GPU-accelerated computing in the cloud with preinstalled NVIDIA drivers, CUDA Toolkit, Nsight suit, GDB & lot more
High-End Ubuntu 22 Desktop - NICE DCV for NVIDIA-GPU 3D instances + CUDA
By NI SP - High-End Remote Desktop and HPC
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.
High-End Ubuntu 20 Desktop - NICE DCV for NVIDIA-GPU 3D instances+ CUDA
By NI SP - High-End Remote Desktop and HPC
Ubuntu 20 Remote Desktop with high-end NICE DCV Remote 3D experience - includes NVIDIA GPU 3D performance drivers and CUDA Toolkit.
The Inference Server - Llama.cpp - CUDA - NVIDIA Container - Ubuntu 22
By NI SP - High-End Remote Desktop and HPC
Run AI Inference on your own server for coding support, creative writing, summarizing, ... without sharing data with other services. The Inference server has all you need to run state-of-the-art inference on GPU servers. Includes llama.cpp inference, latest CUDA and NVIDIA Docker container support. Support for llama-cpp-python, Open Interpreter, Tabby coding assistant.
Customer reviews
No customer reviews yet
Be the first to write a review for this product.