OpenVINO 2022.2 Release

OpenVINO 2022.2がリリースされました。

下記の様にパッケージの選択方法が変更されており、Offline installer は無く、PIPやGitでインストールとなっています。
こちらインストール出来次第、情報を掲載します。

こちらはリリース情報となります。
https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino-relnotes.html

Broader model and hardware support – Optimize & deploy with ease across an expanded range of deep learning models including NLP, and access AI acceleration across an expanded range of hardware.
- NEW: Support for Intel 13^th Gen Core Processor for desktop (code named Raptor Lake).
- NEW: Preview support for Intel’s discrete graphics cards, Intel® Data Center GPU Flex Series and Intel® Arc™ GPU for DL inferencing workloads in intelligent cloud, edge and media analytics workloads. Hundreds of models enabled.
- NEW: Test your model performance with preview support for Intel 4^thGeneration Xeon® processors (code named Sapphire Rapids).
- Broader support for NLP models and use cases like text to speech and voice recognition. Reduced memory consumption when using Dynamic Input Shapes on CPU. Improved efficiency for NLP applications.
Frameworks Integrations – More options that provide minimal code changes to align with your existing frameworks
- OpenVINO Execution Provider for ONNX Runtime gives ONNX Runtime developers more choice for performance optimizations by making it easy to add OpenVINO with minimal code changes.
- NEW: Accelerate PyTorch models with ONNX Runtime using OpenVINO™ integration with ONNX Runtime for PyTorch (OpenVINO™ Torch-ORT). Now PyTorch developers can stay within their framework and benefit from OpenVINO performance gains.
- OpenVINO Integration with TensorFlow now supports more deep learning models with improved inferencing performance.
More portability and performance – See a performance boost straight away with automatic device discovery, load balancing & dynamic inference parallelism across CPU, GPU, and more.
- NEW: Introducing new performance hint (”Cumulative throughput”) in AUTO device, enabling multiple accelerators (e.g. multiple GPUs) to be used at once to maximize inferencing performance.
- NEW: Introducing Intel® FPGA AI Suite support which enables real-time, low-latency, and low-power deep learning inference in this easy-to-use package