The AWS Deep Learning AMIs are available on Ubuntu 18.04, Ubuntu 16.04, Amazon Linux 2, and Amazon Linux with TensorFlow 1.15, Tensorflow 2.0, PyTorch 1.3.1, Also new in this version is support for AWS Neuron, a SDK for running inference using AWS Inferentia chips. It consists of a compiler, run-time, and profiling tools that enable developers to run high-performance and low latency inference using Inferentia-based EC2 Inf1 instances. Neuron is pre-integrated into popular machine learning frameworks including TensorFlow, Pytorch, and MXNet to deliver optimal performance of EC2 Inf1 instances. Customers using Amazon EC2 Inf1 instances will receive the highest performance and lowest cost for machine learning inference in the cloud, and no longer need to make the sub-optimal tradeoff between optimizing for latency or throughput when running large machine learning models in production.

The second, a Base AMI, available in Amazon Linux and Ubuntu versions, provides a high-performance foundational platform for power users to run their own customized deep learning models. The Conda-based AMI comes packaged with latest official releases of the following deep learning frameworks: Apache MXNet 0.12 with Gluon, TensorFlow 1.4, Caffe2 0.8.1, PyTorch 0.2, CNTK 2.2, Theano 0.9, Keras 1.2.2 and Keras 2.0.9. The Base AMI provides the foundation of following GPU drivers and libraries: CUDA 8 and 9, CuBLAS 8 and 9, CuDNN 6 and 7, glibc 2.18, OpenCV 3.2.0, Both of the new AMIs available from the AWS Marketplace include the following libraries and drivers for GPU acceleration on the cloud: CUDA 8 and 9, cuDNN 6 and 7, NCCL 2.0.5 libraries and. To assist with installation of the AMI version that best fits your needs, we have added wizard directly in the AWS console, created a step-by-step guide and provided additional how-to resources in our new documentation site.