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Deep Learning Base AMI (Ubuntu)

The AMI comes pre-installed with the foundational building blocks of deep learning. This includes NVidia CUDA libraries, GPU drivers, and low-level system libraries to scale and accelerate machine learning operations on AWS EC2 instances. You can use this AMI as a clean slate to deploy your customized deep learning set up. For example, for developers contributing to open source deep learning framework enhancements or even building out a new cloud-first deep learning engine, the Base AMI provides the foundation to install your own custom configurations and code repositories to test out new framework features. You could also be an AI startup with a highly specialized deep learning setup that needs a foundation to run on a cloud-scale infrastructure.The AMI Ids for the Deep Learning Base AMI (Ubuntu) are the following:us-east-1 ami-f346c289 us-east-2 ami-9e745afbus-west-2 ami-a1e534d9eu-west-1 ami-9d10b9e4ap-southeast-2 ami-d400e8b6ap-northeast-2 ami-19e04777ap-northeast-1 ami-f6902790Release tags/Branches used:CUDA 8 and 9CuBLAS 8 and 9CuDNN 6 and 7 glibc 2.18 OpenCV 3.2.0NVIDIA driver 384.81NCCL 2.0.5Python 2 and 3The Base AMI comes with the CUDA 9 environment installed by default, however you can also switch to a CUDA 8 environment using simple one-line commands. Check the AMI docsite for more how-to guides and resources on the Deep Learning Base AMI: http://docs.aws.amazon.com/dlami/latest/devguide/what-is-dlami.html


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    Latest Version

    1.0


    Operating System

    Linux/Unix, Ubuntu 16.04


    Delivery Method

    64-bit Amazon Machine Image (AMI) (Read more)



    AWS Services Required

    Amazon EC2, Amazon EBS


    Highlights

    • Used Ubuntu 16.04 (ami-cd0f5cb6) as the base AMI.
    • Comes with CUDA 8 and 9, CuBLAS 8 and 9, CuDNN 6 and 7, glibc 2.18, OpenCV 3.2.0, NVIDIA driver 384.81, NCCL 2.0.5, Python 2 and 3
    • Provides foundational building blocks of deep learning. You can use this AMI as a clean slate to deploy your customized deep learning set up. Comes with CUDA 9 configured by default that can be easily switched to CUDA 8 through simple shell commands

    Product Description

    The AMI comes pre-installed with the foundational building blocks of deep learning. This includes NVidia CUDA libraries, GPU drivers, and low-level system libraries to scale and accelerate machine learning operations on AWS EC2 instances. You can use this AMI as a clean slate to deploy your customized deep learning set up.

    For example, for developers contributing to open source deep learning framework enhancements or even building out a new cloud-first deep learning engine, the Base AMI provides the foundation to install your own custom configurations and code repositories to test out new framework features. You could also be an AI startup with a highly specialized deep learning setup that needs a foundation to run on a cloud-scale infrastructure.

    The AMI Ids for the Deep Learning Base AMI (Ubuntu) are the following:
    us-east-1 ami-f346c289
    us-east-2 ami-9e745afb
    us-west-2 ami-a1e534d9
    eu-west-1 ami-9d10b9e4
    ap-southeast-2 ami-d400e8b6
    ap-northeast-2 ami-19e04777
    ap-northeast-1 ami-f6902790

    Release tags/Branches used:
    CUDA 8 and 9
    CuBLAS 8 and 9
    CuDNN 6 and 7
    glibc 2.18
    OpenCV 3.2.0
    NVIDIA driver 384.81
    NCCL 2.0.5
    Python 2 and 3

    The Base AMI comes with the CUDA 9 environment installed by default, however you can also switch to a CUDA 8 environment using simple one-line commands. Check the AMI docsite for more how-to guides and resources on the Deep Learning Base AMI: http://docs.aws.amazon.com/dlami/latest/devguide/what-is-dlami.html

    Product Details

    • Version: 1.0
    • Available on AWS Marketplace Since: 11/15/2017

    Usage Instructions

    To connect to the operating system, use SSH and the username ubuntu. You can find additional information in the README. /home/ubuntu/src/README.md

    Support Details

    Deep Learning Base AMI (Ubuntu)

    Support is available through forums, technical FAQs and the Service Help Dashboard. Paid support is available.

    https://forums.aws.amazon.com/forum.jspa?forumID=30

    AWS Infrastructure

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    Refund Policy

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    End User License Agreement

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