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

Comes with pre-installed deep learning frameworks and their source code in a unified, shared python environment. Includes Apache MXNet, Caffe, Caffe2, TensorFlow, PyTorch, Theano, CNTK, Torch and Keras as well as NVidia CUDA 8, cuDNN 5.1 and NVIDIA Driver 375.66 packages. It is designed to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. 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.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 typeCheck out the AMI Developer Guide for how-to guides, detailed release notes and additional resources for the Deep Learning AMI with Source Code: http://docs.aws.amazon.com/dlami/latest/devguide/what-is-dlami.html


    Customer Rating

    (10 Customer Reviews)
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    4 star:

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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 support
    • 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

    Comes with pre-installed deep learning frameworks and their source code in a unified, shared python environment. Includes Apache MXNet, Caffe, Caffe2, TensorFlow, PyTorch, Theano, CNTK, Torch and Keras as well as NVidia CUDA 8, cuDNN 5.1 and NVIDIA Driver 375.66 packages. It is designed to provide a stable, secure, and high performance execution environment for deep learning applications running on Amazon EC2. 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.

    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

    Check out the AMI Developer Guide for how-to guides, detailed release notes and additional resources for the Deep Learning AMI with Source Code: http://docs.aws.amazon.com/dlami/latest/devguide/what-is-dlami.html

    Product Details

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

    Resources

    Usage Instructions

    Getting-started guide for Deep Learning AMI: http://docs.aws.amazon.com/dlami/latest/devguide/gs.html

    Read more

    Support Details

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

    Support is available through forums, technical FAQs and the Service Help Dashboard. Post your questions to the AWS Deep Learning AMI Discussion Forum

    https://forums.aws.amazon.com/forum.jspa?forumID=263

    AWS Infrastructure

    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. Learn more

    Refund Policy

    The Deep Learning AMI is provided free of charge

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End User License Agreement (EULA).

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    You will have an opportunity to review your order before launching or being charged.

    Pricing Information

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    Pricing Details

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