Intel OpenVINO 2022.2 is available

Key Updates includes:

Broader Model & Hardware Support

  • Preview support for upcoming Intel® processors, including the Intel® Data Center GPU Flex Series and Intel® Arc™ GPU
  • Support for 4th Gen Intel® Xeon Scalable processor (code named Sapphire Rapids)
  • Reduced memory consumption when using dynamic shapes on CPU to improve efficiency of NLP applications

Portability and Performance

Introducing new performance hint “Cumulative throughput” in AUTO device plug-in, enabling multiple accelerators (e.g. multiple GPUs) to be used at once maximizing inferencing performance.

To download the latest release, do take a look at Intel® Distribution of OpenVINO™ Toolkit

Intel Distribution OpenVINO Toolkit 2022.1 is available!

For more information, do take a look at Intel® Distribution of OpenVINO™ Toolkit

Updated, Cleaner API

  • The new OpenVINO API 2.0 was introduced, which aligns OpenVINO inputs and outputs with frameworks. Input and output tensors use native framework layouts and element types. 
  • The API parameters in Model Optimizer have been reduced to minimize complexity. Performance has been significantly improved for model conversion on Open Neural Network Exchange (ONNX*) models.

Broader Model Support

  • With Dynamic Input Shapes capabilities on CPU, OpenVINO is able to adapt to multiple input dimensions in a single model providing more complete NLP support. Support for Dynamic Shapes on additional XPUs is expected in a future dot release.
  • New models with a focus on NLP and a new category, Anomaly Detection, and support for conversion and inference of select PaddlePaddle* models:
    • Pretrained models for anomaly segmentation focus on industrial inspection making speech denoising trainable, plus updates on speech recognition and speech synthesis
    • Combined demonstration that includes noise reduction, speech recognition, question answering, translation, and text to speech
    • Public models with a focus on NLP ContextNet, Speech-Transformer, HiFi-GAN, Glow-TTS, FastSpeech2, and Wav2Vec

Portability and Performance

  • New AUTO plug-in self-discovers available system inferencing capacity based on model requirements so applications no longer need to know their compute environment in advance.
  • Automatic batching functionality via code hints automatically scale batch size based on XPU and available memory.
  • Built with 12th generation Intel® Core™ processors (formerly code named Alder Lake) in mind. Supports the hybrid architecture necessary to deliver enhancements for high performance inferencing on CPUs and integrated GPUs.

Learn to Accelerate TensorFlow on Intel® Architecture with Minimal Code Changes

The OpenVINO™ integration with TensorFlow enables you to speed up the TensorFlow workflow by adding just two lines of code. Enhance performance on Intel platforms while using the familiar TensorFlow APIs. Download this whitepaper to get started.

Do sign up and get the white papers Learn to Accelerate TensorFlow on Intel® Architecture with Minimal Code Changes