OpenVINO Software Toolkit

OpenVINO is an open-source software toolkit for optimizing and deploying deep learning models. VINO stands for Open Visual Inference and Neural Network Optimization. It is a powerful toolkit designed to optimize and accelerate deep learning models, offering enhanced performance for AI applications.

Intel Corporation develops this toolkit with advanced capabilities the toolkit boosts the performance of AI and deep learning workloads across various hardware.

OpenVINO Features

OpenVINO optimizes deep learning models, improving inference speeds. It supports a wide range of Intel hardware, including CPUs, GPUs, and VPUs. By utilizing a multi-tiered approach to optimize models, OpenVINO ensures faster execution and greater efficiency. Furthermore, its compatibility with popular AI frameworks, such as TensorFlow and PyTorch, simplifies integration for developers.

Acceleration

The OpenVINO toolkit is designed to speed up AI inference by offering lower latency and higher throughput. It helps maintain accuracy, reduce model size, and optimize hardware performance. This toolkit simplifies AI development and the integration of deep learning across fields such as computer vision, large language models (LLM), and generative AI.

Support for Various Models

Work with models developed using well-known frameworks like PyTorch, TensorFlow, ONNX, Keras, PaddlePaddle, and JAX/Flax. Seamlessly integrate models created with transformers and diffusers from the Hugging Face Hub through Optimum Intel.

Model optimizer

One of the standout features of OpenVINO is its Model optimizer, which allows you to convert pre-trained models into an optimized format. This process reduces the size and complexity of the model, ultimately increasing inference speed and reducing resource usage.

How to install OpenVINO ?

OpenVINO installation on Windows using pip:

/> pip install openvino==<version>

replace <version> with the latest version of the OpenVINO toolkit.

OpenVINO Runtime API

The toolkit offers the OpenVINO Runtime API. It is a set of programming interfaces that allows developers to deploy and run deep learning models optimized with the OpenVINO toolkit. It provides an efficient and flexible framework to execute inference workloads on various Intel hardware platforms, including CPUs, GPUs, VPUs, etc. The Runtime API is designed to offer high performance and low-latency execution, making it ideal for applications in areas such as computer vision, AI, and machine learning.

 

More information at:

• https://github.com/openvinotoolkit/openvino