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ibmz-accelerated-for-tensorflow

TensorFlow is an open source machine learning framework. It has a comprehensive set of tools that enable model development, training, and inference. It also features a rich, robust ecosystem.

On IBM® z16™ and later (running Linux on IBM Z or IBM® z/OS® Container Extensions (IBM zCX)), TensorFlow core Graph Execution will leverage new inference acceleration capabilities that transparently target the IBM Integrated Accelerator for AI through the IBM z Deep Neural Network (zDNN) library. The IBM zDNN library contains a set of primitives that support Deep Neural Networks. These primitives transparently target the IBM Integrated Accelerator for AI on IBM z16™ and later. No changes to the original model are needed to take advantage of the new inference acceleration capabilities.

Note. When using IBM Z Accelerated for TensorFlow on either an IBM z14™ or an IBM z15™, TensorFlow will transparently target the CPU with no changes to the model.

See IBM Z Accelerated for TensorFlow for more information

This image is built by IBM to run on the IBM Z architecture and is not affiliated with any other community that provides a version of this image.


License

View license information here

As with all Docker images, these likely also contain other software which may be under other licenses (such as Bash, etc from the base distribution, along with any direct or indirect dependencies of the primary software being contained).

As for any pre-built image usage, it is the image user's responsibility to ensure that any use of this image complies with any relevant licenses for all software contained within.


Versions

Use the pull string below for the version of this image you require.
1.4.1 docker pull icr.io/ibmz/ibmz-accelerated-for-tensorflow@sha256:173fb451e3c80c88e5b1b930031b84de07d93ace97a064b4de27b437eb4e09be Vulnerability Report07-30-2025
Version Pull String Security (IBM Cloud) Created

Usage Notes

For documentation and samples for the IBM Z Accelerated for TensorFlow container image, please visit the GitHub Repository here.