New in AWS Deep Learning AMIs: PyTorch 1.0, MXNet 1.3.1, Chainer 5.1, and CUDA 10
The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with newer versions of the following deep learning frameworks: PyTorch 1.0, MXNet 1.3.1, and Chainer 5.1. This release also includes upgrades of the NVIDIA stack, including CUDA 10, cuDNN 7.4.1, and NCCL 2.3.7. For GPU-based training, PyTorch 1.0 in the AMIs is fully configured to take advantage of performance improvements in CUDA 10.
The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with newer versions of the following deep learning frameworks: PyTorch 1.0, MXNet 1.3.1, and Chainer 5.1. This release also includes upgrades of the NVIDIA stack, including CUDA 10, cuDNN 7.4.1, and NCCL 2.3.7. For GPU-based training, PyTorch 1.0 in the AMIs is fully configured to take advantage of performance improvements in CUDA 10.
AWS Deep Learning AMIs also support other popular frameworks and interfaces including TensorFlow, Keras, Gluon, and Microsoft Cognitive Toolkit (CNTK) — 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. When you activate a Conda environment, the Deep Learning AMIs automatically deploy higher-performance builds of frameworks, optimized for the EC2 instance of your choice. 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.