add example script for docker-machine testing with aws

examples/docker-machine-aws.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+
+# define the following env vars first:
+# AWS_ACCESS_KEY_ID
+# AWS_SECRET_ACCESS_KEY
+# AWS_DEFAULT_REGION
+
+# Instance types: see https://aws.amazon.com/ec2/instance-types/
+# and pricing: https://aws.amazon.com/ec2/pricing/on-demand/
+
+# defaults to --amazonec2-root-siez of 16gbs (16 GB EBS disk storage)
+# on a ubuntu-based AMI
+
+docker-machine create \
+	--driver amazonec2 \
+	--amazonec2-instance-type p2.xlarge \
+	aws-gpu
+
+docker-machine restart aws-gpu
+docker-machine ssh aws-gpu
+
+sudo usermod -aG docker $USER
+
+# Install official NVIDIA driver package
+sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
+sudo sh -c 'echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/cuda.list'
+sudo apt-get update && sudo apt-get install -y --no-install-recommends linux-headers-generic dkms cuda-drivers
+
+# Add the package repositories
+curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
+  sudo apt-key add -
+distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
+curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
+  sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+sudo apt-get update
+
+# Install nvidia-docker2 and reload the Docker daemon configuration
+sudo apt-get install -y nvidia-docker2
+sudo pkill -SIGHUP dockerd
+
+# Add the nvidia-docker 2.0 package repositories
+curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
+  sudo apt-key add -
+distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
+curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
+  sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+sudo apt-get update
+
+# Install nvidia-docker2 and reload the Docker daemon configuration
+sudo apt-get install -y nvidia-docker2
+sudo pkill -SIGHUP dockerd
+
+# Test nvidia-smi with the latest official CUDA image
+docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi