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This product has charges associated with it for seller support. The Deep Learning OSS Nvidia Driver AMI (Amazon Linux 2) Version 79.0 provides an optimized environment for deploying cutting-edge deep learning applications in the AWS EC2 cloud. With pre-installed NVIDIA drivers, TensorFlow, PyTorch, and other essential libraries, this AMI enables developers to accelerate model training and inference seamlessly. The robust support for GPU instances facilitates high-performance computing tasks, making it ideal for data scientists, researchers, and machine learning engineers. Users can leverage the scalability of AWS infrastructure to manage workloads of any size, ensuring efficient resource utilization. Whether you're building complex neural networks or analyzing massive datasets, this AMI simplifies the deployment process, allowing you to focus on innovation and experimentation.
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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 OSS Nvidia Driver AMI (Amazon Linux 2) Version 79.0 provides a robust environment for building and deploying deep learning models using NVIDIA's advanced GPU technology. Built on the most recent Amazon Linux 2 base, this AMI is optimized for performance and offers seamless integration with NVIDIA drivers and libraries.
Features
- Pre-installed NVIDIA Drivers: Ensure high performance and stability with the latest NVIDIA GPU drivers pre-configured for scalable cloud-based workloads.
- Optimized for Deep Learning Frameworks: Along with NVIDIA drivers, deep learning frameworks such as TensorFlow, PyTorch, and MXNet are readily available, allowing for quick model development.
- Amazon Linux 2 Support: Built on a secure and stable platform, this AMI benefits from long-term support and various AWS optimizations for improved compatibility and performance.
Benefits
- Faster Model Training and Inference: Leverage GPU acceleration to significantly reduce training times for deep learning models, enabling faster iterations and deployment.
- Cost-effective Solution: By utilizing the flexibility of EC2 instances with this AMI, users can optimize resource allocation and manage costs effectively through on-demand scalability.
- Easy to Launch and Manage: Simplifies the deployment process, allowing data scientists and ML engineers to set up their environments quickly and focus on model development rather than infrastructure.
Use Cases
- Research and Development: Ideal for researchers seeking to conduct experiments in deep learning without the hassle of setup and configuration.
- Production Workloads: Suitable for organizations deploying machine learning applications in production environments that require reliable and scalable computational resources.
- Education and Training: Perfect for academic purposes, enabling students and educators to explore and teach deep learning concepts in a ready-to-use environment.
Harness the power of GPU-accelerated computing with the Deep Learning OSS Nvidia Driver AMI (Amazon Linux 2) Version 79.0, designed for efficiency, performance, and ease of use in your deep learning projects.
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Highlights
- The Deep Learning OSS Nvidia Driver AMI (Amazon Linux 2) Version 79.0 is engineered to seamlessly integrate with NVIDIA GPUs, ensuring optimal performance for deep learning applications. By pre-installing essential libraries and frameworks such as TensorFlow and PyTorch, this AMI allows data scientists and AI developers to accelerate model training and inference, reducing time-to-market for machine learning projects.
- With enhanced support for NVIDIA's CUDA Toolkit, this AMI leverages the full potential of GPU resources, enabling sophisticated computations that are crucial for AI workloads. Its compatibility with Amazon EC2 instances ensures flexibility in scaling applications; users can easily launch instances tailored to varying project demands and optimize costs by using reserved or spot instances for extensive training sessions.
- This AMI serves as an ideal solution for research institutions and enterprises focused on advanced machine learning tasks. Users can benefit from out-of-the-box configurations that simplify the setup process while ensuring compliance with the latest deep learning standards. Additionally, the continual updates to the AMI provide users with the latest driver and library enhancements, ensuring sustained performance and security.
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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