New in AWS Deep Learning AMIs: Optimized TensorFlow 1.12 and MMS 1.0
The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with an optimized build of TensorFlow 1.12 and support for MMS 1.0, a Model Server for Apache MXNet that provides a flexible and easy way to serve deep learning models exported from MXNet or the Open Neural Network Exchange (ONNX). For Amazon EC2 C5 instances, Deep Learning AMIs deploy compute-optimized TensorFlow built with Intel Advanced Vector Extensions (AVX instruction sets) to speed up the performance of vector and floating point operations. The AMIs also come pre-configured to leverage Intel Math Kernel Library for Deep Neural Networks (MKL-DNN). Training a ResNet-50 benchmark with the synthetic ImageNet dataset using our optimized build of TensorFlow 1.12 on a c5.18xlarge instance type was 13x faster than training using the stock TensorFlow 1.12 binaries.
AWS Deep Learning AMIs also support other popular frameworks including PyTorch, MXNet, and Chainer — all pre-installed and fully-configured for you to start developing your deep learning models in minutes while taking full advantage of the computational power of Amazon EC2 instances. For a complete list of frameworks and versions supported by the AWS Deep Learning AMI, see the release notes.
Get started quickly with the AWS Deep Learning AMIs using the getting-started guides and beginner to advanced level tutorials in our developer guide. You can also subscribe to our discussion forum to get launch announcements and post your questions.