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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.
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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 ARM64 Base OSS Nvidia Driver GPU AMI is designed to help developers and researchers utilize the power of NVIDIA GPUs on ARM64 architecture effectively. Built on Ubuntu 22.04, this AMI comes pre-integrated with essential deep learning frameworks and NVIDIA drivers, providing a robust environment for machine learning and AI projects.
Key Features:
- NVIDIA GPU Support: Pre-installed NVIDIA drivers optimized for ARM64 architecture, ensuring maximum performance and efficiency for deep learning tasks.
- Deep Learning Frameworks: Includes popular frameworks such as TensorFlow, PyTorch, and others, ready for immediate use, to accelerate your AI model development.
- Ubuntu 22.04 Base: Leverages the stable and secure Ubuntu 22.04 base, making it easy to install additional packages and tools as needed for your project.
- Optimized Runtime Environment: Configured for high-performance training and inference, making the most of available hardware resources.
Benefits:
- Quick Deployment: Launch instances rapidly with a pre-configured environment tailored for deep learning workloads, significantly reducing setup time.
- Cost-Effective: Pay only for what you use while leveraging the power of NVIDIA GPUs to accelerate computations, ultimately lowering overall processing time and costs.
- Flexible Use Cases: Ideal for researchers, data scientists, and developers looking to build, train, and deploy machine learning models efficiently or run GPU-accelerated applications.
Potential Use Cases:
- Research and Development: Perfect for academic and commercial research projects in AI and machine learning, enabling rapid experimentation and model testing.
- Production Workflows: Seamlessly integrate into production environments for real-time inference and large-scale data processing tasks.
- Education and Training: Utilize in educational settings for teaching deep learning concepts and practical applications.
Harness the power of deep learning on ARM64 architecture today with the Deep Learning ARM64 Base OSS Nvidia Driver GPU AMI and accelerate your AI journey.
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Highlights
- This AMI provides a powerful base for deep learning applications, specifically optimized for ARM64 architecture with Ubuntu 22.04. It comes pre-installed with the NVIDIA driver, allowing for high-performance GPU computation. Developers can quickly deploy their models with ease, benefiting from an environment tailored for both research and production workloads in AI and machine learning.
- Utilizing the latest advancements in NVIDIA GPU technology, this AMI enables efficient utilization of resources, making it ideal for complex computation tasks. Users can leverage CUDA and cuDNN libraries for accelerated performance on deep learning frameworks. This setup significantly reduces the configuration time, enabling teams to focus on model development and experimentation rather than infrastructure management.
- Perfect for startups, research institutions, and businesses, this AMI caters to diverse use cases in deep learning, computer vision, and natural language processing. Its versatility and compatibility with various deep learning frameworks such as TensorFlow and PyTorch allow developers to drive innovation efficiently. With the ARM64 architecture, users can harness cost-effective scalability for their applications in cloud environments.
Details
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Delivery method
Delivery option
64-bit (Arm) 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 (g5g.4xlarge) in the US East (N. Virginia) Region. View pricing details
$1.948/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 |
|---|---|---|---|
m6g.medium | $0.14 | $0.038 | $0.178 |
m6g.large | $0.14 | $0.077 | $0.217 |
m6g.xlarge | $0.28 | $0.154 | $0.434 |
m6g.2xlarge | $0.56 | $0.308 | $0.868 |
m6g.4xlarge | $1.12 | $0.616 | $1.736 |
m6g.8xlarge | $2.24 | $1.232 | $3.472 |
m6g.12xlarge | $3.36 | $1.848 | $5.208 |
m6g.16xlarge | $4.48 | $2.464 | $6.944 |
m6g.metal | $3.36 | $2.464 | $5.824 |
m6gd.medium | $0.14 | $0.045 | $0.185 |
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 (Arm) 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 'ubuntu' using the key specified at launch.
OS commands via SSH: SSH as user 'ubuntu' 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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