New AWS Deep Learning AMIs for Machine Learning Practitioners
We’re pleased to announce the availability of two new versions of the AWS Deep Learning AMIs. The first, a Conda-based AMI, available in Amazon Linux and Ubuntu versions, is for developers who need ready-to-run deep learning environments with Python support. 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.
We’re pleased to announce the availability of two new versions of the AWS Deep Learning AMIs. The first, a Conda-based AMI, available in Amazon Linux and Ubuntu versions, is for developers who need ready-to-run deep learning environments with Python support. 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 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, NVIDIA driver 384.81, NCCL 2.0.5, and Python 2 and 3.
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. NVidia Driver 384.81. 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.