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This product has charges associated with it for seller support. The Deep Learning Base OSS Nvidia Driver AMI (Amazon Linux 2) Version 67.2 is optimized for developers and data scientists to accelerate their deep learning workflows. Pre-configured with essential libraries and the latest Nvidia drivers, this AMI facilitates seamless deployment of machine learning models and research applications. Its efficient architecture ensures maximum performance on GPU instances, making it ideal for training complex models and conducting large-scale data processing tasks. Use cases include computer vision, natural language processing, and reinforcement learning projects. Whether you're a startup innovating in AI or an established enterprise looking to harness cloud capabilities, this AMI provides a robust foundation for your deep learning initiatives in the Amazon EC2 environment.
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Overview
This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.
The Deep Learning Base OSS Nvidia Driver AMI (Amazon Linux 2) Version 67.2 is designed for developers and researchers leveraging deep learning frameworks in cloud environments.
Features
- Optimized Environment: Pre-configured with essential deep learning libraries and frameworks such as TensorFlow, PyTorch, and MXNet, ensuring a streamlined setup for machine learning projects.
- Nvidia GPU Support: Includes the latest Nvidia drivers tailored for Amazon EC2 GPU instances, enabling optimal performance for compute-intensive tasks.
- Amazon Linux 2: Built on a stable and secure version of Amazon Linux 2, offering long-term support along with access to a rich ecosystem of AWS services.
- Performance Monitoring: Comes equipped with tools for real-time performance monitoring and visualization, facilitating quicker debugging and iteration of models.
Benefits
- Reduced Setup Time: Significantly decreases the time needed to set up your deep learning environment, allowing you to focus on model development and experimentation.
- Scalable: Easily scalable to accommodate varying workloads, from small-scale experiments to large-scale training sessions, with the flexibility of EC2 instances.
- Community Support: Leverage a robust community and extensive documentation for troubleshooting and knowledge sharing.
Use Cases
- Research and Development: Ideal for academic and commercial research focusing on AI and machine learning, enabling teams to prototype and deploy models at scale.
- Data Science Projects: Perfect for data scientists who require a powerful infrastructure for data preprocessing, model training, and analysis.
- High-Performance Computing: Suitable for organizations looking to run compute-intensive simulations, leveraging the power of GPU instances for faster results.
Utilize the Deep Learning Base OSS Nvidia Driver AMI to supercharge your deep learning workflows in the AWS cloud, ensuring a reliable and efficient development experience.
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Highlights
- The Deep Learning Base OSS Nvidia Driver AMI (Amazon Linux 2) Version 67.2 provides a robust environment for developers leveraging deep learning frameworks. Pre-configured with essential libraries, this AMI streamlines the setup process, allowing for quick deployment of models. With optimized Nvidia drivers, users can maximize GPU performance, resulting in faster training and inference times for complex models.
- This AMI supports popular deep learning frameworks, such as TensorFlow, PyTorch, and MXNet, facilitating seamless integration into existing workflows. By utilizing this image, teams can focus more on model development and less on environment management. The compatibility and ease of use make it a preferred choice for research projects and production deployments across various industries.
- Ideal for both beginners and experienced practitioners, the Deep Learning Base OSS AMI enables users to leverage powerful compute resources on the AWS EC2 cloud. Use cases include image and speech recognition, natural language processing, and autonomous systems. The flexibility offered by the AWS ecosystem, combined with this AMI, allows organizations to scale their data science initiatives efficiently.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
AmazonLinux 2
Typical total price
This estimate is based on use of the seller's recommended configuration (g4dn.4xlarge) in the US East (N. Virginia) Region. View pricing details
$2.324/hour
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.
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Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t1.micro | $0.07 | $0.02 | $0.09 |
t2.nano | $0.07 | $0.006 | $0.076 |
t2.micro AWS Free Tier | $0.21 | $0.012 | $0.222 |
t2.small | $0.07 | $0.023 | $0.093 |
t2.medium | $0.14 | $0.046 | $0.186 |
t2.large | $0.14 | $0.093 | $0.233 |
t2.xlarge | $0.28 | $0.186 | $0.466 |
t2.2xlarge | $0.56 | $0.371 | $0.931 |
t3.nano | $0.07 | $0.005 | $0.075 |
t3.micro AWS Free Tier | $0.07 | $0.01 | $0.08 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
Fees for this product are not refundable. The instance can be terminated at any time to stop incurring charges.
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
System Updates
Additional details
Usage instructions
SSH to the instance and login as 'ec2-user' using the key specified at launch.
OS commands via SSH: SSH as user 'ec2-user' to the running instance and use sudo to run commands requiring root access.
More on using Deep Learning AMI with Conda: https://docs.aws.amazon.com/dlami/latest/devguide/tutorial-conda.html
Resources
Vendor resources
Support
Vendor support
Email support for this AMI is available through the following: https://supportedimages.com/support/ OR support@supportedimages.com
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.
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