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 a deep learning framework that is designed for efficiency and flexibility. It allows you to mix the flavors of symbolic programming and imperative programming to maximize efficiency and productivity. At 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 the scheduler makes symbolic execution fast and memory efficient. The library is portable and lightweight, and it scales to multiple NVIDIA GPUs and multiple machines.
More than a deep learning project, Apache MXNet is a collection of blueprints and guidelines that are used to build deep learning systems and provide interesting insights about deep learning systems for hackers.
In the container, go to the
/workspace/README.md directory for information about customizing your Optimized Deep Learning Framework image. For more information about Apache MXNet, including tutorials, documentation, and examples, see:
This document provides information about the key features, software enhancements and improvements, known issues, and how to run this container.