Nnef tagged news

Neural network standard streamlines machine learning tech development

Several neural network frameworks for deep learning exist, all of which offer distance features and functionality. Transferring neural networks between frameworks, however, creates extra time and work for developers. The Khronos Group has developed NNEF (Neural Network Exchange Format), an open, royalty-free standard that allows hardware manufacturers to reliably exchange trained neural networks between training frameworks and inference engines. Learn more about NNEF on the Vision Systems Design blog.

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.

Khronos Releases New NNEF Convertors, Extensions, and Model Zoo

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 enables NNEF files to contain richer networks 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 Home Page.

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.

All of the presentations and videos from the Khronos OpenVX workshop at the 2019 Embedded Vision Summit are now online. If you were unable to attend this workshop, you may now watch the seven sessions online and follow along with the slide presentations:

  • Introduction and OpenCL Overview & Update – Neil Trevett, NVIDIA: slides, video
  • OpenCL & SYCL – Andrew Richards, Codeplay: slides, video
  • Intel Open Source SYCL Compiler Project – Konstantin S. Bobrovsky, Intel: slides, video
  • OpenVX Presentations – Frank Brill, Cadence / Niclas Danielsson & Mikael Pendse, Axis : here & here, video
  • Inference with OpenVX – Mike Schmit, AMD: slides, video
  • NNEF Presentation – Gergely Debreczeni, AImotive: slides, video
  • OpenVX Hands-On - Part 1 – Rajy Rawther & Kiriti Nagesh Gowda, AMD: slides, video

Adding Machine Learning based Image Processing to your Embedded Product with NNEF

Khronos member Au-Zone Technologies has written a guest post on the CNX Embedded Software blog showing how to add Machine Learning (ML) processing to an embedded product with the help from the Khronos Groups Neural Network Exchange Format (NNEF). The post illustrates, with an example implementation, how to detect and classify different pasta types on a moving conveyor belt.

AImotive’s aiWare3 Hardware IP Helps Drive Autonomous Vehicles To Production with Khronos’ NNEF

AImotive, the global provider of full stack, vision-first self-driving technology, today announced the release of aiWare3, the company’s 3rd generation, scalable, low-power, hardware Neural Network (NN) acceleration core. The scalable aiWare3 architecture facilitates low-power continuous operation for autonomous vehicles (AVs) with up to 12 or more high-resolution cameras, LiDARs and/or radar. aiWare3 delivers up to 50 TMAC/s (> 100 TOPS) per chip at more than 2 TMAC/s (4 TOPS) per W1. aiWare3’s IP core is supported by a comprehensive software development kit (SDK) that uses The Khronos Group’s NNEF standard. It will ship to lead customers in Q1 2019.

AImotive's aiWare3 Hardware IP Helps Drive Autonomous Vehicles Towards Production.

Neil Trevett, President of the Khronos Group, delivers the presentation “Update on Khronos Standards for Vision and Machine Learning” at the Embedded Vision Alliance’s September 2018 Vision Industry and Technology Forum. Neil Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the deployment of embedded vision and AI. For the full version of this video, along with hundreds of others on various embedded vision topics, please visit the Embedded Vision website.

Khronos member Peter McGuinness has written an overview about NNEF over on the GFXSpeak blog. The new standard was released in provisional form in December of 2017 and, after a period of consultation with industry, is now ratified in its final form and available for immediate use. As well as the standard itself, Khronos is simultaneously releasing a suite of open source tools to allow developers to immediately begin using the format with the three most popular training frameworks: Tensorflow and Caffe/Caffe2. All of these tools are available on GitHub in the Khronos repo. Learn more about NNEF.

The Khronos Group announces updates to key standards and opens the Khronos Education Forum at SIGGRAPH. With various Khronos events throughout the week, including a day of Birds of a Feather (BOF) sessions and its annual networking reception, Khronos is accelerating open standards ecosystems and continuing its commitment to the SIGGRAPH community of interactive graphics professionals. At SIGGRAPH, Khronos will be talking about the following standards developments and initiatives: NNEF 1.0 Specification Finalized, OpenXR Demonstrates Specification in Hardware Implementation, Ecosystem Grows; New Extensions Released and a Call for Participation - Education Forum Opens for Public Contribution. In addition to standards updates, The Khronos Group is hosting educational sessions and networking events this week, including a full-day of BOF sessions with talks from various members.

The Khronos Group announces the ratification and the public release of the NNEF™ 1.0 (Neural Network Exchange Format) specification. After gathering feedback from the industry review of the provisional specification, Khronos releases NNEF 1.0 as a stable, flexible, and extensible open standard for hardware manufacturers to reliably deploy optimized, accelerated neural network inferencing onto diverse edge devices. Together with this release, an ecosystem of tools is now also available on GitHub, including an NNEF parser and converters from Tensorflow and Caffe. Importers into popular inferencing environments, including Android’s Neural Network API (NNAPI) and Khronos’ OpenVX™, are also being developed.