Sold by: Supported Images
AWS Free Tier
This product has charges associated with it for seller support. The Deep Learning Proprietary Nvidia Driver AMI (Amazon Linux 2) Version 79.0 is specifically designed for developers and data scientists looking to accelerate their deep learning workflows in the cloud. This AMI comes pre-installed with the latest Nvidia drivers optimized for high-performance GPU computing, ensuring seamless integration with popular deep learning frameworks such as TensorFlow and PyTorch. By leveraging the power of Amazon EC2 instances, users can quickly scale their applications, conduct model training, and fine-tune algorithms efficiently. Ideal for research institutions and enterprises alike, this AMI streamlines the environment setup process, allowing users to focus on innovation and deployment while reducing operational overhead. Harness the full potential of your deep learning projects with this specialized Amazon Linux 2 AMI.
Sold by: Supported Images
Overview
This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.
The Deep Learning Proprietary Nvidia Driver AMI (Amazon Linux 2) Version 79.0 is engineered for professionals looking to harness the power of GPU-accelerated applications for deep learning and AI workloads. This AMI integrates the latest Nvidia drivers with Amazon Linux 2, providing an optimized environment for rapid deployments and high-performance computation.
Key Features:
- Pre-installed Nvidia Drivers: Seamlessly utilizes Nvidia GPUs for enhanced performance in deep learning applications.
- Compatibility with Popular Frameworks: Supports TensorFlow, PyTorch, and other major frameworks, enabling developers to build and deploy models efficiently.
- Optimized for Performance: Configured for superior processing speeds and reduced latency, ideal for training complex neural networks.
- Amazon Linux 2 Integration: Leverages the stability and security of Amazon Linux 2, ensuring a robust and reliable foundation for your AI projects.
- 64-bit Architecture: Fully supports the latest 64-bit software ensuring compatibility with cutting-edge machine learning libraries.
Benefits:
- Accelerated Development: Rapidly spin up deep learning environments without the hassle of driver installations and compatibility checks.
- Access to Extensive Resources: Tap into resources that facilitate quick experimentation, validation, and deployment of AI models.
- Cost-effective Scalability: Easily scale your computational resources in the cloud, optimizing costs as your projects grow.
Use Cases:
- Machine Learning Research: Ideal for researchers and developers working on innovative AI technologies, needing powerful compute resources.
- Big Data Analytics: Leverage advanced analytics and machine learning on large datasets seamlessly.
- Production-Level AI Solutions: Deploy models directly into production environments where performance and reliability are paramount.
Elevate your deep learning projects with the Deep Learning Proprietary Nvidia Driver AMI, designed to provide an efficient, powerful, and easy-to-manage environment for all your AI needs.
Try our most popular AMIs on AWS EC2
- Ubuntu 24.04 AMI on AWS EC2
- Ubuntu 22.04 AMI on AWS EC2
- Ubuntu 20.04 AMI on AWS EC2
- Ubuntu 18.04 AMI on AWS EC2
- CentOS 9 AMI on AWS EC2
- CentOS 8 AMI on AWS EC2
- CentOS 7 AMI on AWS EC2
- Debian 12 AMI on AWS EC2
- Debian 11 AMI on AWS EC2
- Debian 10 AMI on AWS EC2
- Debian 9 AMI on AWS EC2
- Red Hat Enterprise Linux 9 (RHEL 9) AMI on AWS EC2
- Red Hat Enterprise Linux 8 (RHEL 8) AMI on AWS EC2
- Red Hat Enterprise Linux 7 (RHEL 7) AMI on AWS EC2
- Oracle Linux 9 AMI on AWS EC2
- Oracle Linux 8 AMI on AWS EC2
- Oracle Linux 7 AMI on AWS EC2
- Amazon Linux 2023 AMI on AWS EC2
- Windows 2022 Server AMI on AWS EC2
- Windows 2019 Server AMI on AWS EC2
- Docker on Ubuntu 20 AMI on AWS EC2
- Docker on CentOS 7 AMI on AWS EC2
Highlights
- The Deep Learning Proprietary Nvidia Driver AMI (Amazon Linux 2) Version 79.0 is meticulously optimized for high-performance computing tasks. With pre-installed Nvidia drivers, it allows seamless integration with popular deep learning frameworks such as TensorFlow and PyTorch. Users can harness the full computational power of Nvidia GPUs, enabling rapid training and inference for complex models, significantly reducing development time and enhancing productivity.
- This AMI is particularly beneficial for organizations looking to deploy AI applications quickly and efficiently. With native support for popular deep learning frameworks like TensorFlow, PyTorch, and MXNet, it facilitates seamless integration and development. Users can harness the power of powerful GPU instances to run experiments, fine-tune models, and deploy AI solutions at scale, ultimately accelerating time-to-market and improving productivity.
- Utilizing the Deep Learning Proprietary Nvidia Driver AMI not only simplifies setup but also ensures compatibility with the latest AI advancements, keeping pace with the evolving deep learning landscape. Its integration with Amazon EC2 allows users to scale resources elastically as their computational demands grow. By leveraging AWS's robust infrastructure, users can cost-effectively manage workloads, optimizing both performance and budget for large-scale AI deployments and training processes.
Details
Sold by
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 (g3.4xlarge) in the US East (N. Virginia) Region. View pricing details
$2.26/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.
- ...
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.
Similar products
Deep Learning AMI DLAMI Ubuntu 18.04 LTS | Support by SupportedImages
By Supported Images
This product has charges associated with it for seller support. The Deep Learning AMI DLAMI Ubuntu 18.04 LTS is a powerful and flexible Amazon Machine Image designed for deep learning and AI development in the cloud. Pre-configured with popular frameworks such as TensorFlow, PyTorch, and MXNet, this AMI enables developers to streamline their machine learning workflows. It supports GPU instances for accelerated performance, making it ideal for training complex models quickly. With extensive documentation and community support, users can easily deploy and manage their deep learning applications. Suitable for data scientists, researchers, and developers, this AMI accelerates experimentation and innovation in machine learning projects, providing a robust environment to tackle various data-driven challenges effectively. Leverage the power of AWS to scale your AI initiatives with ease.
Deep Learning AMI DLAMI Ubuntu 16.04 LTS | Support by SupportedImages
By Supported Images
This product has charges associated with it for seller support. The Deep Learning AMI DLAMI Ubuntu 16.04 LTS is designed for developers and data scientists looking to streamline the deployment of deep learning applications on AWS EC2. This AMI comes pre-installed with popular deep learning frameworks such as TensorFlow, PyTorch, and MXNet, enabling rapid experimentation and model training. With GPU support for accelerated performance, users can efficiently process large datasets, making it ideal for tasks ranging from image recognition to natural language processing. Additionally, the image is optimized for easier integration with AWS services like S3 and SageMaker. Whether you're prototyping ML models or running production workloads, the DLAMI Ubuntu 16 provides a versatile, scalable solution for all your deep learning needs.
DLAMI Neuron TensorFlow 2.10 Ubuntu 20 | Support by SupportedImages
By Supported Images
This product has charges associated with it for seller support. The Deep Learning AMI Neuron TensorFlow 2.10 (Ubuntu 20.04) provides an optimized platform for developing and training deep learning models in the cloud using TensorFlow 2.10. Designed for high performance, this AMI integrates Amazon's Neuron SDK, enabling efficient deployment on AWS Inferentia chips. With pre-installed frameworks and libraries, users can quickly set up their machine learning environments, significantly reducing time-to-market. Ideal for researchers and data scientists, this AMI supports diverse use cases including computer vision, natural language processing, and reinforcement learning. Leverage the scalability of Amazon EC2 to dynamically adjust resources as project demands evolve, ensuring cost efficiency without sacrificing performance. Whether you're a seasoned ML engineer or a novice, this AMI simplifies deep learning workflows, enhancing productivity and innovation.
This is a repackaged software product wherein additional charges apply for support by Bansir with Deep Learning AMI (DLAMI) Amazon Linux 2 and includes support.
DLAMI ARM Base OSS Nvidia GPU Ubuntu 22 | Support by SupportedImages
By Supported Images
This product has charges associated with it for seller support. The Deep Learning ARM64 Base OSS Nvidia Driver GPU AMI (Ubuntu 22.04) is designed for developers and researchers who require a robust environment for advanced machine learning tasks. This Amazon Machine Image (AMI) leverages ARM64 architecture for optimized performance and is pre-configured with essential deep learning frameworks, including TensorFlow and PyTorch, as well as the latest Nvidia drivers. Users can quickly launch multiple EC2 instances to scale their deep learning experiments and leverage the power of GPU acceleration, enhancing training times and processing capabilities. Ideal for data scientists, AI developers, and businesses looking to deploy AI solutions, this AMI simplifies the setup process and ensures a seamless experience for demanding computational workloads. Explore deep learning without the hassle of manual configurations.
Customer reviews
No customer reviews yet
Be the first to write a review for this product.