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.
OpenVINO is a comprehensive toolkit for developing applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends CV workloads across Intel hardware, maximizing performance. OpenVINO enables CNN-based deep learning inference on the edge; supports heterogeneous execution across computer vision accelerators—CPU, GPU, Intel Movidius Neural Compute Stick, and FPGA—using a common API; and includes optimized calls for OpenCV and OpenVX.
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.
The Embedded Vision Alliance has posted a follow-on article showcasing several case study examples of OpenVX implementations in various applications, leveraging multiple hardware platforms along with both traditional and deep learning computer vision algorithms. The article also introduces readers to an industry alliance created to help product creators incorporate practical computer vision capabilities into their hardware and software, along with outlining the technical resources that this alliance provides. A companion article focuses on more recent updates to the OpenVX API, up to and including latest v1.2 of the specification and associated conformance tests, along with the recently published set of extensions that OpenVX implementers can optionally provide. It also discusses the optimization opportunities available with SoCs’ increasingly common heterogeneous computing architectures.
Khronos member Cadence Design Systems, and ArcSoft, announced they have partnered to develop AI and vision applications for Cadence Tensilica Vision DSPs. The OpenVX conformant Vision P6 DSP supports AI applications developed in the Caffe, TensorFlow and TensorFlowLite frameworks through the Tensilica Xtensa Neural Network Compiler, Android Neural Network API for on-device AI acceleration in Android-powered devices and includes complete, optimized support for more than 1,500 OpenCV-based vision and OpenVX 1.1 library functions.
The Khronos Group standards logos are now available for download on Sketchfab. Sketchfab makes it easy for anyone to publish and find 3D content online. Available logos currently include OpenXR, OpenCL, NNEF, OpenVX, SPIR, Vulkan, WebGL, SYCL and glTF. OpenGL has not been overlooked and will be arriving shortly.
Synopsys, Inc. announced a new release of its DesignWare ARC MetaWare EV Development Toolkit. The ARC MetaWare EV Development Toolkit offers a programming environment for the EV6x vision processor IP based on the OpenVX open standard API, with a C/C++ compiler and OpenCL C vectorizing compiler. The Toolkit includes OpenVX kernels optimized to run on EV6x Processors, the first hardware-software platform to successfully pass The Khronos Group’s OpenVX 1.2 conformance tests.
The Khronos™ Group is working with Au-Zone Technologies to enable NNEF™ (Neural Network Exchange Format) files to be easily used with leading machine learning training frameworks. NNEF enables the optimized ingestion of trained neural networks into hardware inference engines on a diverse range of devices and platforms. Au-Zone is working with the Khronos NNEF Working Group to implement two purpose-built bidirectional converters, between TensorFlow and NNEF and also Caffe2 and NNEF. Both converters are expected to be released as open source projects to the development community in Q3 2018 under the Apache 2.0 license.
The curriculum for the 2018 OpenVX Workshop at the Embedded Vision Summit in May has been finalized. The Khronos Group will be presenting a day-long hands-on workshop all about OpenVX cross-platform neural network acceleration API for embedded vision applications. Khronos has developed a new curriculum making this a do-not-miss tutorial with new information on computer vision algorithms for feature tracking and neural networks mapped to the graph API. The tutorials will be presented by speakers from Khronos member companies AMD, Axis Communications, Cadence and Codeplay. There will be hands-on practice sessions with the folks who created the OpenVX API to give participants a chance to solve real computer vision problems. Discussions will also include the OpenVX roadmap and what’s to come. Registration is now open but space is limited, so be sure not to wait too long.
Don’t miss this year’s OpenVX Workshop at Embedded Vision Summit on May 24th, 2018. Khronos will present a day-long hands-on workshop all about OpenVX cross-platform neural network acceleration API for embedded vision applications. We’ve developed a new curriculum so even if you attended in past years, this is a do-not-miss, jam-packed tutorial with new information on computer vision algorithms for feature tracking and neural networks mapped to the graph API. We’ll be doing a hands-on practice session that gives participants a chance to solve real computer vision problems using OpenVX with the folks who created the API. We’ll also be talking about the OpenVX roadmap and what’s to come.
Don’t miss this year’s OpenVX Workshop at Embedded Vision Summit. Khronos will present a day-long hands-on workshop all about OpenVX cross-platform neural network acceleration API for embedded vision applications. We’ve developed a new curriculum so even if you attended in past years, this is a do-not-miss, jam-packed tutorial with new information on computer vision algorithms for feature tracking and neural networks mapped to the graph API. We’ll be doing a hands-on practice session that gives participants a chance to solve real computer vision problems using OpenVX with the folks who created the API. We’ll also be talking about the OpenVX roadmap and what’s to come. Registration is now open. Early bird pricing ends April 10th.
Registration now open for the Khronos Standards for Neural Networks and Embedded Vision workshop at the Embedded Vision Summit in Santa Clara. Early bird pricing is now $99. This seminar is intended for engineers, researchers, and software developers who develop vision and neural network applications and want to benefit from transparent HW acceleration. Also, managers that want to get a general understanding of the structure and uses of Khronos standards.
VeriSilicon today announced significant milestones have been achieved for its versatile and highly scalable neural network inference engine family VIP8000. The fully programmable VIP8000 processors reach the performance and memory efficiency of dedicated fixed-function logic with the customizability and future proofing of full programmability in OpenCL, OpenVX, and a wide range of NN frameworks including NNEF. “The biggest thing to happen in the computer industry since the PC is AI and machine learning, it will truly revolutionize, empower, and improve our lives. It can be done in giant machines from IBM and Google, and in tiny chips made with VeriSilicon’s neural network processors,” said Dr. Jon Peddie, president Jon Peddie Research. “By 2020 we will wonder how we ever lived without our AI assistants,” he added.
The Khronos Group announces the release of the Neural Network Exchange Format (NNEF™) 1.0 Provisional Specification for universal exchange of trained neural networks between training frameworks and inference engines. NNEF reduces machine learning deployment fragmentation by enabling a rich mix of neural network training tools and inference engines to be used by applications across a diverse range of devices and platforms. The release of NNEF 1.0 as a provisional specification enables feedback from the industry to be incorporated before the specification is finalized — comments and feedback are welcome on the NNEF GitHub repository.