Menu
Apache MXNet on AWS
Developer Guide

Deep Learning CUDA 9 AMI Amazon Linux Version: 1.0

Deep Learning Amazon Machine Image

The Deep Learning AMIs are prebuilt with CUDA9 and MXNet and also contain the Anaconda Platform(Python2 and Python3).

Highlights of the Release

  1. Used Amazon Linux 2017.09 (ami-8c1be5f6) as the base AMI

  2. CUDA 9

  3. CuDNN 7

  4. NCCL 2.0

  5. CUDA 9 support

  6. MXNet with CUDA9 Support

Prebuilt Deep Learning Frameworks

  • MXNet: MXNet is a flexible, efficient, portable and scalable open source library for deep learning. It supports declarative and imperative programming models, across a wide variety of programming languages, making it powerful yet simple to code deep learning applications. MXNet is efficient, inherently supporting automatic parallel scheduling of portions of source code that can be parallelized over a distributed environment. MXNet is also portable, using memory optimizations that allow it to run on mobile phones to full servers.

    • branch/tag used: v0.12.0 Release Candidate tag

    • Justification: Stable and well tested

    • Source_Directories:

      • /home/ec2-user/src/mxnet

  • Caffe2: Caffe2 is a cross-platform framework made with expression, speed, and modularity in mind.

    • branch/tag used: v0.8.1 tag

    • Justification: Stable and well tested

    • Note: Available for Python2.7 only

    • Source_Directories:

      • For Python2.7+ - /home/ec2-user/src/caffe2

      • For Anaconda Python2.7+ - /home/ec2-user/src/caffe2_anaconda2

  • TensorFlow: TensorFlow™ is an open source software library for numerical computation using data flow graphs.

    • branch/tag used : Master tag

    • Justification : Stable and well tested

    • Source_Directories :

      • For Python2.7+ - /home/ec2-user/src/tensorflow

      • For Python3+ - /home/ec2-user/src/tensorflow3

      • For Anaconda Python2.7+ - /home/ec2-user/src/tensorflow_anaconda

      • For Anaconda Python3+ - /home/ec2-user/src/tensorflow_anaconda3

Python 2.7 and Python 3.5 Support

Python 2.7 and Python 3.5 are supported in the AMI for the following Deep Learning Frameworks:

  1. MXNet

  2. Caffe2

  3. Tensorflow

CPU Instance Type Support

The AMI supports CPU Instance Types for all frameworks. MXNet is built with support for Intel MKL2017 DNN library support.

GPU Drivers Installed

  • CuDNN 7

  • Nvidia 384.81

  • CUDA 9.0

Launching Deep Learning Instance

Choose the flavor of the AMI from the list below in the region of your choice and follow the steps at:

EC2 Documentation to launch P2 Instance

Testing the FrameWorks

The Deep Learning frameworks have been tested with MNIST data. The AMI contains scripts to train and test with MNIST for each of the frameworks.

The scripts are available in the /home/ec2-user/src/bin directory.

The following scripts test the various frameworks:

/home/ec2-user/src/bin/testMXNet : tests MXNet

/home/ec2-user/src/bin/testTensorFlow : tests TensorFlow

/home/ec2-user/src/bin/testCaffe2 : tests Caffe2

The following tests have been run against each of the frameworks:

  • MXNet: This example inside the MXNet repository. Validation accuracy threshold tested for is 97%.

  • Tensorflow: This example inside the keras repository. Validation accuracy threshold tested for is 95%.

  • Caffe2: Based on this example inside the Caffe2 repository. Validation accuracy threshold is 90%.

Amazon Linux AMI

Amazon Linux based Deep Learning AMIs are available in the following regions:

  • eu-west-1(DUB)

  • us-east-1(IAD)

  • us-west-1(PDX)

  • us-east-2(CHM)

  • ap-southeast-2(SYD)

  • ap-northeast-1(NRT)

  • ap-northeast-2(ICN)

References

MXNet

Test Environments

  • Built on p2.16xlarge.

  • Also tested on p2.xlarge, c4.4xlarge.