The QtBase dev branch, which will become Qt 5.12, now has experimental Vulkan support, courtesy of MoltenVK and prior work in Qt. When the MoltenVK Vulkan to Metal translation library was open sourced earlier this year, this opened the question of how to make this work with Qt. Check out the Qt blog to learn how support for MoltenVK was accomplished.
The X-Plane cross-platform flight simulator has been depending upon OpenGL for nearly two decades since the program first came into existence, but a port of its rendering engine to use the Vulkan API has been a work-in-progress. It looks like their Vulkan support is getting squared away as the company has tweeted this weekend they will be talking about Vulkan integration this weekend at the Flight Sim Expo in Las Vegas.
Yesterday Valve released Vulkan support for Dota 2 on macOS. Indeed, this first major game relying upon MoltenVK for mapping Vulkan over the Apple Metal drivers is delivering performance gains. Phoronix has started to post some benchmarks.
Qualcomm Technologies debuted the Qualcomm Snapdragon XR1 Platform, a dedicated Extended Reality (XR) platform during a launch event leading up to the Augmented World Expo (AWE). The integrated display processor provides a range of display options with hardware accelerated composition, dual-display support, 3D overlays and support for leading graphics Application Programming Interfaces (API), including OpenGL, OpenCL and Vulkan.
Vulkan support for DOTA2 on macOS is now available. Yielding improved performance and frame time stability. You will need to enable the "Vulkan support" DLC in Steam, switch to Vulkan in the game video settings, and then, if you experience any issues, please report them on Github.
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 last week announced the launch of a project with Au-zone of Calgary, Canada to produce two conversion tools that will allow developers to import NNEF files into TensorFlow and Caffe2 as well as export NNEF files from those training frameworks. In line with Khronos’ recent policy, the tools will be made available in the second half of 2018 as open source projects on Github where contributions from the open source community will be welcomed. These tools will join the converters for Caffe and Tensorflow (which has two formats to consider) and the NNEF parser that are all already available.
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. Additionally, the NNEF and OpenVX Working Groups are working closely within Khronos to develop open-source importers, using the OpenVX Kernel Import extension, to enable the ingestion and execution of NNEF files.