Skip to main content

Openvx tagged news

In this EE Times Europe article, Neil Trevett describes how the need for graphics and compute acceleration in embedded markets is growing. Cameras and sensor arrays are increasingly central to many use cases in diverse industries, ranging from automotive to industrial, and are generating increasingly rich data streams that require sophisticated processing. At the same time, advanced user interfaces are being developed using high-quality 3D graphics and even augmented-reality technology. However, the need to deploy accelerated processing, combined with the complexities of safety-critical certification, has created a confusing landscape of processors, accelerators, compilers, APIs, and libraries. That has driven up integration costs for embedded accelerators, which in turn has constrained innovation and time-to-market efficiencies.

Open standards have an important role in helping hardware and software vendors navigate this complex technology environment. Acceleration standards for the embedded market can enable cross-platform software reusability, decouple software and hardware development for easier deployment and integration of new components, provide cross-generation reusability, and facilitate field upgradability. Such standards reduce costs, shorten time to market, and lower the barriers to using advanced techniques such as inferencing and vision acceleration in compelling real-world products.

Khronos Group President, Neil Trevett, shares how open standards have an important role mitigating the complexities of safety-critical certification in a confusing landscape of processors, accelerators, compilers, APIs, and libraries, that drive up integration costs for embedded accelerators, which in turn has constrained innovation and time-to-market efficiencies.

Join us to help drive the evolution of Machine Learning acceleration standards. ML developers lament the growing fragmentation in the ML ecosystem. Khronos knows that open and royalty-free standards can play an essential role in reducing fragmentation, reducing costs, and providing the industry participants the opportunity to grow. Based on feedback from previous summit and discussions, Khronos is creating a coalition of interested parties to meet the needs of the ML community for hardware acceleration.

The Khronos Group and VeriSilicon are holding a joint Technical Tutorial and Workshop in Shanghai on April 22 & 23rd. The first day will be a virtual event and will include an overview of the Khronos Group and then deep dive into Vulkan and Vulkan Ray Tracing. On day 2, which will be onsite in Shanghai, the workshop will focus on OpenXR and parallel processing, vision acceleration and inferencing. Be sure to check out the event’s page for more information and register.

In this interview, authors Victor Erukhimov, Frank Brill, Stephen Ramm and Radhakrishna Giduthuri are asked about their new book OpenVX Programming Guide, and uncover the unique quality a book can have from being written by a team of authors.

What is the approach of your book that will help the reader get the most out of OpenVX?

The book starts with the introduction to the OpenVX high level concepts, and then discusses each functional block by solving a model problem, reviewing in detail the sample code that is available on GitHub.

OpenVX is a mature computer vision and machine learning API standard by the Khronos group, developed to be a novel, open and royalty-free standard for cross-platform acceleration. In this webinar, aimed at engine and middleware developers, application developers, and embedded compute engineers, we will present the latest features in OpenVX 1.3 and how these features are being leveraged by OpenVX adopters. Join Neil Trevett, President of the Khronos Group and Kiriti Nagesh Gowda, OpenVX Working Group chair on October 14th. Please sign-up early as space is limited.

The “OpenVX Programming Guidebook” presents definitive information on OpenVX 1.2 and 1.3, the Neural Network, and other extensions as well as the OpenVX Safety Critical standard. This book will give a high-level overview of the OpenVX standard, its design principles, and overall structure. It covers computer vision functions and the graph API, providing examples of usage for the majority of the functions. It is intended both for the first-time user of OpenVX and as a reference for experienced OpenVX developers. The book is currently available from Amazon and Elsevier.

Today The Khronos Group, announces the ratification and public release of the OpenVX™ 1.3 specification, along with code samples and a prototype conformance test suite. OpenVX is a royalty-free open standard for portable, optimized, and power-efficient vision and machine learning inferencing acceleration, vital to embedded and real-time use cases, such as face-, body-, and gesture-tracking, smart video surveillance, advanced driver assistance systems, object and scene reconstruction, augmented reality, visual inspection, robotics, and more. Also available today is an open source implementation of OpenVX 1.3 for Raspberry Pi to make OpenVX widely accessible to developers. The new specification can be found on the OpenVX registry.

Today The Khronos Group announces the ratification and public release of the OpenVX™ 1.3 specification, along with code samples and a prototype conformance test suite. OpenVX is a royalty-free open standard for portable, optimized, and power-efficient vision and machine learning inferencing acceleration, vital to embedded and real-time use cases, such as face-, body-, and gesture-tracking, smart video surveillance, advanced driver assistance systems, object and scene reconstruction, augmented reality, visual inspection, robotics, and more. Also available today is an open source implementation of OpenVX 1.3 for Raspberry Pi to make OpenVX widely accessible to developers. The new specification can be found on the OpenVX registry. Read the press release for more details and give Khronos feedback on the OpenVX community forums.

Today The Khronos Group announces a significant expansion in the ecosystem for the NNEF™ (Neural Network Exchange Format) open, royalty-free standard that enables hardware manufacturers to reliably exchange trained neural networks between training frameworks and inference engines. New and improved NNEF open source convertors, including for TensorFlow Lite and ONNX, enables NNEF to be used to carry trained frameworks from a wider range of training frameworks. A set of extensions to the NNEF 1.0 specification enable NNEF files to contain a richer network of operations and topologies. Finally, an openly available NNEF Model Zoo enables inferencing engines to test their reliable import of NNEF models. More information on NNEF can be found at the NNEF Home Page.