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.
Another blog explaining Vulkan synchronization has just been posted by @Themaister. Synchronization in Vulkan is a large hurdle to overcome when learning the API, and rather than mechanically explaining how it works, the goal in this blog is to instil a mental model in the reader. Despite its reputation for maddening complexity, it is actually understandable and quite logical once you get over the initial hurdles.
Frank Brill, Design Engineering Director at Cadence, presents the “Portable Performance via the OpenVX Computer Vision Library: Case Studies” tutorial at the May 2019 Embedded Vision Summit. For the full version of this video, along with hundreds of others on various embedded vision topics, please visit the Embedded Vision website.
As part of its unwavering commitment to open source and open standards, Collabora is proud to be part of bringing the recently-releasedOpenXR 1.0 to life. We are pioneering the Monado open source runtime for OpenXR to ensure the future of XR is truly open and accessible to all hardware vendors. With the release of OpenXR 1.0, we were able to publish the few changes required to adapt Monado to the 1.0 API, which will be our target ABI from here on. Learn more about Monado and Collabora’s work on OpenXR.