IBM Z Accelerated for TensorFlow is a containerized solution that harnesses the benefits of TensorFlow and optimized to run on IBM Z and IBM LinuxONE platforms.
TensorFlow is currently the most popular open-source deep learning framework, with widespread adoption in industry and research. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that facilitates easy building and deployment of ML-powered applications. TensorFlow can be used across a range of tasks including training and inference of deep neural networks. TensorFlow makes it faster and easier for developers to implement machine learning models, as it assists the process of acquiring data, serving predictions at scale, and refining future results.
On IBM Z and IBM LinuxONE, TensorFlow is built to exploit the vector architecture for inference operations. Recently, we announced the general availability of new capabilities that enable TensorFlow to directly leverage the on-chip AI inference accelerator featured in IBM z16 and LinuxONE Emperor 4. On z16 hardware, TensorFlow can now leverage new inference acceleration capabilities with IBM Z Accelerated for TensorFlow container image.
What is IBM Z Accelerated for TensorFlow?
With IBM z16, IBM has brought the Telum processor featuring a dedicated on-chip AI accelerator focused on delivering high-speed, real-time inferencing at scale to market. This feature is designed to accelerate the compute intensive operations commonly found in deep learning models.
With IBM Z Accelerated for TensorFlow, we have enabled one of the most popular open-source frameworks for AI to leverage the IBM z16 Integrated Accelerator for AI. We have developed a high-performance plugin to TensorFlow called IBM-zDNN-Plugin, which allows accelerated deployment of TensorFlow models on IBM z16 hardware. The acceleration is enabled through Custom Ops, Kernels, and a Graph Optimizer that get registered within TensorFlow.
On IBM Z and IBM LinuxONE, TensorFlow has the same ‘look and feel’ as any other platform. You can continue to build and train your TensorFlow models on the platform of your choice – whether x86, cloud, or IBM zSystems. TensorFlow models trained on other platforms are portable to IBM Z and IBM LinuxONE. With IBM Z Accelerated for TensorFlow, you can now bring TensorFlow models to IBM z16 and exploit the Integrated Accelerator for AI without any changes to the model.
IBM Z Accelerated for TensorFlow enables real-time inferencing across a massive number of transactions with negligible latency. As one example (of many), this can give customers the ability to screen all their credit card transactions for fraud (in real time) and react quickly enough to prevent the fraud from happening in the first place.
How to get started
IBM Z and LinuxONE Container Image Registry (ICR) includes open-source software in container images that are often used as the foundation for new composite workloads. ICR provides a secure and trustworthy content source. On the IBM Z and LinuxONE Container Registry, the IBM Z Accelerated for TensorFlow image is freely available. The image runs in both the Linux and zCX environments of z/OS on IBM Z.
We’ve provided a detailed documentation on deployment, model validation, execution on Integrated Accelerator for AI, modifying default execution paths, etc. We have also provided sample scripts and detailed tutorial that includes download and setup instructions, as well as steps that assist with running the samples using the container. For samples and tutorials please visit the github repository here.
Technical support can be availed with AI Toolkit for IBM Z and IBM LinuxONE - a family of popular open-source AI frameworks with IBM Elite Support and adapted for IBM Z and IBM LinuxONE hardware. Information regarding technical support can be found here. Additionally, IBM Client Engineering for Systems has a no-charge discovery workshop that can help you get jump started on leveraging capabilities like TensorFlow on IBM Z and IBM LinuxONE.