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Use New Features in Intel® Extension for TensorFlow* on CPUs & GPUs

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Overview

Intel® Extension for TensorFlow* is an extension of the stock, open source TensorFlow library, which is uniquely optimized for performant deep learning on Intel CPUs and GPUs.

This session focuses on how you can increase AI and deep learning workload performance by taking advantage of new CPU and GPU functionalities in the latest TensorFlow extension.

What you will learn:

  • Get an overview of the new features and benefits, plus how to use them for CPU and GPU.
  • How to use the open source machine learning compiler, OpenXLA, with Intel Extension for TensorFlow.
  • How to switch the CPU back end (Threading Building Blocks [TBB] and OpenMP*) with Intel Extension for TensorFlow.

Skill level: Intermediate

 

Featured Software

Get the stand-alone version of Intel Extension for TensorFlow from GitHub* or as part of the Intel® AI Analytics Toolkit.

 

Download Code Samples

  • Get Started with Intel Extension for TensorFlow and Intel Optimization for TensorFlow
  • Optimize a Pretrained TensorFlow Model for Inference
  • TensorFlow* Training Optimizations with Intel® Advanced Matrix Extensions Bfloat16

See All Code Samples

 

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Intel® AI Analytics Toolkit

Accelerate data science and AI pipelines—from preprocessing through machine learning—and provide interoperability for efficient model development.

 

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Related Articles & Blogs

An Introduction to Intel Extension for TensorFlow

Use Deep Learning Optimizations from Intel in TensorFlow

Run a TensorFlow Stable Diffusion on Intel® Arc™ GPUs

Create Your First Neural Network with Python* and TensorFlow

Related On-Demand Videos & Webinars

Get Better TensorFlow Performance on CPUs and GPUs

Accelerate Deep Learning with Intel Extension for TensorFlow

Enhance Deep Learning Workloads on the Latest Intel® Xeon® Processors

Related Podcast

How Two Students Built an AI Chatbot Using TensorFlow and oneAPI

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