NVIDIA Optimized Deep Learning Framework, powered by Apache MXNet Overview

The NVIDIA Deep Learning SDK accelerates widely-used deep learning frameworks such as Apache MXNet.

Apache MXNet is designed for both efficiency and flexibility. It allows you to mix the flavors of symbolic programming and imperative programming to maximize efficiency and productivity.

In its core is a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. The library is portable and lightweight, and it scales to multiple GPUs and multiple machines.

Apache MXNet is also more than a deep learning project. It is also a collection of blueprints and guidelines for building deep learning systems and interesting insights of deep learning systems for hackers.

See /workspace/README.md inside the container for information on customizing your Optimized Deep Learning Framework image. For more information about Apache MXNet, including tutorials, documentation, and examples, see:

This document describes the key features, software enhancements and improvements, any known issues, and how to run this container.