Deep Learning AMI with Source Code (CUDA 8, Ubuntu)

The Deep Learning AMI is a base Ubuntu image provided by Amazon Web Services for use on Amazon Elastic Compute Cloud (Amazon EC2).It is designed to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. It has popular deep learning frameworks, including MXNet, Caffe, Caffe2, TensorFlow, PyTorch, Theano, CNTK, Torch and Keras as well as packages that enable easy integration with AWS. It also includes Anaconda Data Science Platform for Python2 and Python3. The Deep Learning AMI is provided at no additional charge to Amazon EC2 users.The AMI Ids for the Deep Learning Ubuntu AMI are the following:us-east-1: ami-37bb714dus-east-2: ami-9a416dffus-west-2: ami-f1d51489eu-west-1: ami-dca37ea5ap-southeast-2: ami-985bb9faap-northeast-1: ami-7612cc10ap-northeast-2: ami-e6ca6f88 Release tags/Branches used:MXNet 0.11.0TensorFlow 1.3.0Keras 2.0.8 with TensorFlow as default backendKeras 1.2.2 (DMLC fork) with MXNet as default backend*Caffe 1.0Caffe2 0.8.0 **CNTK 2.0Theano 0.9.0Torch (master branch)PyTorch 0.2.0*Keras 1.2.2 is installed in a Conda-managed virtual environment* *Caffe2 0.8.0 no longer supports g2 instance typeThe AMI is configured with NVidia CUDA 8 and NVidia Driver 375.66. The AMI is NOT compatible with EC2 p3 instance type.Check the AMI release notes for more details: http://docs.aws.amazon.com/dlami/latest/devguide/appendix-ami-release-notes.html


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    Latest Version

    2.4_Oct2017


    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 with CUDA 8, and NVidia Driver 375.66. Please note the AMI is NOT compatible with EC2 p3 instance type. Use Deep Learning AMI CUDA 9 version for p3 instance type.
    • Framework upgrades for Caffe1 (compiled with NCCL 2.0 support), PyTorch, Keras 2.0.
    • 8 Deep Learning Frameworks - contains the most popular Deep Learning Frameworks(MXNet, Caffe, Caffe2, Tensorflow, Theano, Torch, PyTorch and CNTK)

    Product Description

    The Deep Learning AMI is a base Ubuntu image provided by Amazon Web Services for use on Amazon Elastic Compute Cloud (Amazon EC2).It is designed to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. It has popular deep learning frameworks, including MXNet, Caffe, Caffe2, TensorFlow, PyTorch, Theano, CNTK, Torch and Keras as well as packages that enable easy integration with AWS. It also includes Anaconda Data Science Platform for Python2 and Python3. The Deep Learning AMI is provided at no additional charge to Amazon EC2 users.

    The AMI Ids for the Deep Learning Ubuntu AMI are the following:
    us-east-1: ami-37bb714d
    us-east-2: ami-9a416dff
    us-west-2: ami-f1d51489
    eu-west-1: ami-dca37ea5
    ap-southeast-2: ami-985bb9fa
    ap-northeast-1: ami-7612cc10
    ap-northeast-2: ami-e6ca6f88

    Release tags/Branches used:
    MXNet 0.11.0
    TensorFlow 1.3.0
    Keras 2.0.8 with TensorFlow as default backend
    Keras 1.2.2 (DMLC fork) with MXNet as default backend*
    Caffe 1.0
    Caffe2 0.8.0 **
    CNTK 2.0
    Theano 0.9.0
    Torch (master branch)
    PyTorch 0.2.0

    *Keras 1.2.2 is installed in a Conda-managed virtual environment
    * *Caffe2 0.8.0 no longer supports g2 instance type

    The AMI is configured with NVidia CUDA 8 and NVidia Driver 375.66. The AMI is NOT compatible with EC2 p3 instance type.

    Check the AMI release notes for more details: http://docs.aws.amazon.com/dlami/latest/devguide/appendix-ami-release-notes.html

    Product Details

    • Version: 2.4_Oct2017
    • Available on AWS Marketplace Since: 02/10/2017

    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 AMI with Source Code (CUDA 8, 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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