What Is DGL?

Deep Graph Library (DGL) is a Python package built for the implementation and training of graph neural networks on top of existing DL frameworks. The DGL NGC Container is built with the latest versions of DGL, PyTorch, and their dependencies.

What Is DGL Production Branch October 2024?

The DGL Production Branch, exclusively available with NVIDIA AI Enterprise, is a 9-month supported, API-stable branch that includes monthly fixes for high and critical software vulnerabilities. This branch provides a stable and secure environment for building your mission-critical AI applications. The DGL production branch releases every six months with a three-month overlap in between two releases.

Getting started with DGL Production Branch

Before you start, ensure that your environment is set up by following one of the deployment guides available in the NVIDIA AI Enterprise Documentation.

For an overview of the features included in the DGL Production Branch October 2024, please refer to the Release Notes for DGL 24.08.

For a comprehensive collection of resources on DGL, including tutorials, documentation, and examples, visit the following links:

• DGL website

• DGL project

• DGL Documentation

• DGL Tutorials

Additionally, if you're looking for information on Docker containers and guidance on running a container, review the Containers For Deep Learning Frameworks User Guide.

Compatible Infrastructure Software Versions

For the optimized performance, it is highly recommended to deploy the supported NVIDIA AI Enterprise Infrastructure software in conjunction with your AI software.

Production Branch - October 2024 (24h2) is compatible with NVIDIA AI Enterprise Infrastructure 4 and NVIDIA AI Enterprise Infrastructure 5.

Security Vulnerabilities in Open Source Packages

Please review the Security Scanning tab to view the latest security scan results.

For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Known Issues

There is a bug in RAPIDS whereby attempting to serialize any cudf dataframe whose column names are numpy integers will result in a TypeError similar to TypeError: can not serialize 'numpy.int64' object. A fix will be provided in the next Production Branch October 2024 (PB24h2) release. As a workaround, users should rewrite the dataframe column names by getting the underlying int/float value from the numpy type and reassigning that value as the column name.

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NVIDIA AI Enterprise Documentation

Visit the NVIDIA AI Enterprise Documentation Hub for release documentation, deployment guides and more.

NVIDIA Licensing Portal

Go to the NVIDIA Licensing Portal to manage your software licenses.