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This product has charges associated with it for seller support. The Deep Learning ARM64 AMI is optimized for running graphics-intensive applications on EC2 using Nvidia GPUs. Pre-configured with PyTorch 2.3.0, this AMI is designed for developers and researchers in machine learning, enabling rapid experimentation and deployment of deep learning models. It leverages the capabilities of Ubuntu 22.04 for an agile development environment and includes essential libraries and tools, ensuring seamless integration into existing workflows. Ideal for use in academic research, AI-driven startups, or enterprise projects, this AMI helps reduce setup time and maximizes productivity. By choosing this AMI, users can scale their deep learning applications efficiently while benefiting from the power of ARM64 architecture and Nvidia's GPU acceleration.
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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.
Leverage the power of deep learning with our optimized ARM64 AMI designed specifically for NVIDIA GPU utilization. Built on Ubuntu 22.04, this image is pre-installed with PyTorch 2.3.0 and the latest NVIDIA drivers, ensuring seamless performance for your machine learning tasks.
Features:
- Optimized for ARM64 Architecture: Maximize performance on ARM-based instances with tailored configurations for efficient processing.
- NVIDIA Driver Integration: Built-in NVIDIA drivers ensure compatibility and performance optimization for GPU-accelerated applications.
- Pre-installed PyTorch 2.3.0: Start your AI and machine learning projects instantly with the latest version of PyTorch, facilitating rapid prototyping and development.
Benefits:
- Cost-Effective: Leverage low-cost ARM instances without sacrificing performance, suitable for large-scale deep learning models.
- Enhanced Computational Speeds: Unlock significant performance improvements for training and inference tasks using powerful GPU resources.
- Rapid Deployment: Pre-configured environment reduces setup time, enabling you to focus on development rather than configuration.
Use Cases:
- Machine Learning Research: Ideal for researchers and data scientists developing and testing deep learning algorithms.
- University Projects: Perfect for academic institutions needing to provide robust environments for students in AI courses.
- Production-Grade Solutions: Deploy scalable deep learning solutions for real-time inference or batch processing workloads.
Harness the full potential of your GPU resources with this versatile deep learning AMI and accelerate your journey into AI development.
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Highlights
- The Deep Learning ARM64 AMI offers a high-performance environment for executing deep learning workloads. With optimized support for ARM architecture, it provides enhanced efficiency and scalability when deployed on EC2 instances. Users can take full advantage of the GPU-accelerated capabilities of Nvidia drivers, ensuring that computational tasks are handled swiftly and effectively. This AMI is perfect for researchers and developers looking to innovate with deep learning frameworks.
- Pre-installed with PyTorch 2.3.0, this AMI simplifies the setup process for machine learning projects. It enables users to swiftly perform data preprocessing, model training, and inference, thereby accelerating the development lifecycle. The inclusion of Ubuntu 22.04 ensures compatibility with a wide range of tools and libraries, making it easier for teams to integrate this environment into their existing workflows without any friction.
- This AMI is ideally suited for various use cases, including computer vision, natural language processing, and predictive analytics. Its flexible architecture allows for rapid scaling to handle large datasets and complex models, empowering businesses to leverage AI for competitive advantage. Whether you're an academic researcher or an industry professional, integrating this AMI can significantly enhance productivity while reducing infrastructure overhead in cloud computing 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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