AWS Machine Learning Blog

Updated AWS CloudFormation Deep Learning Template Adds New Features and Capabilities

by Naveen Swamy | on | Permalink | Comments |  Share
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AWS CloudFormation, which creates and configures Amazon Web Services resources with a template, simplifies the process of setting up a distributed deep learning cluster. The AWS CloudFormation Deep Learning template uses the latest updated Amazon Deep Learning AMI (which provides Apache MXNet, TensorFlow, Caffe, Theano, Torch, and CNTK frameworks) to launch a cluster of EC2 instances and other AWS resources needed to perform distributed deep learning. AWS CloudFormation creates all resources in the customer account.

We’ve updated the AWS CloudFormation Deep Learning template with exciting additional capabilities including automation to dynamically adjust the cluster to the maximum number of available worker instances when an instance fails to provision (perhaps due to reached limit). This template also lets you choose between GPU and CPU instance types as well as adds support to run under either Ubuntu or Amazon Linux environments for your cluster. We’ve also added the ability to provision a new, or attach an existing Amazon EFS file system to your cluster to let you easily share code/data/logs and results.

To learn more, visit the AWS Labs – Deep Learning GitHub repo and follow the tutorial, where we show how easy it is to run distributed training on AWS using the MXNet and TensorFlow frameworks.