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This product has charges associated with it for seller support. The Deep Learning ARM64 AMI with OSS Nvidia Driver for GPU and PyTorch 2.2.1 on Ubuntu 20.04 provides a powerful platform for developing and deploying advanced machine learning applications. Featuring an optimized setup for ARM64 architecture, this AMI ensures high performance with efficient resource utilization. Pre-installed with essential libraries and frameworks, it simplifies the process of building and training deep learning models. Ideal for data scientists and AI researchers, it supports various use cases including image classification, natural language processing, and more. Benefit from seamless integration with AWS services, allowing for scalable training and inference. Experience the flexibility of a ready-to-use environment that accelerates your deep learning projects while minimizing setup time and operational overhead.
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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 AMI is specifically designed for efficient deployment of deep learning workloads in the cloud. With integrated Nvidia drivers and optimized for GPU performance, this AMI enables high-performance computations tailored for data-intensive applications.
Key Features:
- Pre-Configured Environment: Built on Ubuntu 20.04, this AMI comes with PyTorch 2.2.1 pre-installed, ensuring faster setup and development.
- Nvidia GPU Support: Leverage the power of Nvidia GPUs for accelerated deep learning training and inference processes.
- ARM64 Architecture: Optimized for ARM64, this AMI provides significant performance improvements for compatible workloads, making it a cost-effective choice for scalable applications.
Benefits:
- Enhanced Performance: Maximize throughput for model training and inference with state-of-the-art GPU capabilities.
- Flexibility: Supports a wide range of machine learning and AI frameworks, suitable for research, experimentation, and production deployment.
- Cost Efficiency: Utilize ARM64 architecture for lower resource consumption while maintaining high performance, leading to potential cost savings in cloud resource usage.
Use Cases:
- Research and Development: Ideal for academics and researchers looking to experiment with machine learning models without extensive infrastructure overhead.
- Production Workloads: Suitable for deploying real-time inference services and large-scale training jobs in cloud environments.
- Model Optimization: Engages users who want to optimize their models on cutting-edge hardware with robust software support.
By choosing the Deep Learning ARM64 AMI with Nvidia driver support, users gain a powerful, flexible platform tailored to their deep learning needs, ready to handle today's demanding machine learning challenges.
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Highlights
- The Deep Learning ARM64 AMI is optimized for high-performance computing with ARM architecture, providing an efficient environment for deploying deep learning workloads. Pre-installed with Nvidia drivers, this AMI ensures seamless integration with GPU resources, facilitating accelerated training and inference of deep learning models. Users can harness the power of ARM64 technology to achieve improved performance and energy efficiency in their AI projects.
- Bundled with PyTorch 2.2.1, this AMI simplifies the setup process for machine learning practitioners. PyTorch is a highly flexible and popular framework, enabling users to easily build and deploy neural networks. The provided version ensures compatibility with various libraries and tools, offering a comprehensive ecosystem for research and production workflows, thereby enhancing productivity in developing bespoke deep learning solutions.
- Ideal for researchers, developers, and businesses in the AI domain, this AMI supports a myriad of applications, from natural language processing to computer vision. Its compatibility with Ubuntu 20.04 guarantees users access to a robust, stable operating system, conducive to experimentation and deployment. This makes it an excellent choice for those looking to leverage cloud computing for cutting-edge innovations in artificial intelligence and machine learning.
Details
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Delivery method
Delivery option
64-bit (Arm) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 20.04
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
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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 |
|---|---|---|---|
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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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.
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