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    Deep Learning AMI Neuron Amazon Linux 2023 | Support by SupportedImages

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    AWS Free Tier
    This product has charges associated with it for seller support. The Deep Learning AMI Neuron (Amazon Linux 2023) provides a robust and scalable environment optimized for machine learning practitioners and researchers. Preconfigured with popular frameworks such as TensorFlow and PyTorch, along with the latest NVIDIA CUDA and cuDNN libraries, this AMI enables seamless deployment of deep learning models. With support for Amazon EC2 instances powered by AWS Neuron, users can efficiently compile and optimize their models for inference on AWS Inferentia chips, ensuring high performance and cost-effectiveness. Ideal for developing, training, and deploying cutting-edge AI applications, this AMI streamlines the workflow from concept to production, making it an essential tool for organizations looking to leverage deep learning technology in the cloud.
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    Deep Learning AMI Neuron Amazon Linux 2023 | Support by SupportedImages

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    Overview

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    This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.

    The Deep Learning AMI Neuron (Amazon Linux 2023) offers a powerful environment specifically designed for deep learning model development and training. Built on the latest Amazon Linux, this AMI is optimized for AWS infrastructure and includes pre-installed deep learning frameworks such as TensorFlow, PyTorch, and MXNet.

    Key Features:

    • AWS Neuron SDK: Leverage a set of powerful tools for building high-performance deep learning models on AWS Inferentia chips.
    • Pre-installed Frameworks: Save time by using popular frameworks that come pre-configured and ready to use.
    • Optimized Performance: Designed for efficiency, delivering superior training performance on deep learning tasks.
    • Scalable: Easily scale your machine learning workloads using EC2 instances to meet your project demands.

    Benefits:

    • Streamlined Development: Focus on building and training your models without the hassle of setup and configuration.
    • Cost-Effective: By utilizing the AWS Neuron-powered instances, you can significantly reduce inference costs for your AI applications.
    • Integrated AWS Services: Seamlessly integrate with other AWS services like S3 for storage, SageMaker for model training, and CloudWatch for monitoring.

    Use Cases:

    • Model Development: Ideal for data scientists and engineers looking to develop and test deep learning models efficiently.
    • Research and Prototyping: Suitable for academic research requiring heavy computational resources in a flexible environment.
    • Production Deployment: Optimal for deploying scaled machine learning workloads using AWS Inferentia and EC2 instances for inference tasks.

    Elevate your deep learning projects with the Deep Learning AMI Neuron, designed to harness the full capabilities of AWS for your high-performance computing needs.

    Try our most popular AMIs on AWS EC2

    Highlights

    • The Deep Learning AMI Neuron (Amazon Linux 2023) is tailored for developers and data scientists aiming to create, train, and deploy deep learning models using AWS. It comes pre-installed with high-performance tools and libraries optimized for Amazon EC2, facilitating streamlined workflows. Its support for multiple frameworks allows users to leverage popular libraries such as TensorFlow and PyTorch for enhanced productivity in building complex AI solutions.
    • With the Deep Learning AMI Neuron, users can quickly scale their applications, taking advantage of AWS's infrastructure to manage large datasets efficiently. The AMI is designed for optimal performance with AWS Inferentia and Trainium chips, which accelerate training and inference tasks. This capability is especially beneficial for industries requiring real-time insights, such as finance, healthcare, and autonomous systems.
    • Security and reliability are central to the Deep Learning AMI Neuron, featuring compatibility with AWS's security tools to safeguard data and models. The AMI benefits from regular updates and patches from AWS, ensuring users have access to the latest advancements and enhancements in machine learning. This makes it an ideal choice for enterprises looking to innovate rapidly while maintaining robust security and efficiency in their deployment processes.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    AmazonLinux 2023

    Typical total price

    This estimate is based on use of the seller's recommended configuration (inf2.8xlarge) in the US East (N. Virginia) Region. View pricing details

    $4.208/hour

    Pricing

    Deep Learning AMI Neuron Amazon Linux 2023 | Support by SupportedImages

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    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.

    Usage costs (597)

     Info
    • ...
    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.

    Usage information

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    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  https://awsdocs-neuron.readthedocs-hosted.com/en/latest/dlami/index.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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