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.
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.