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AMDVLK 2022.Q3.5 adds support for the VK_EXT_depth_clamp_zero_one extension, performance tuning for Doom Eternal and Yquake2 and other games, enables acquire-release barrier support, and enables MSAA anti-aliasing decompression using the compute engine. The driver has also been built against the Vulkan API 1.3.228 headers.
Recently the open-source AMD OpenGL driver “RadeonSI” enabled OpenGL threading by default for the “glthread” option that has long been opt-in on a per-game/app basis. Along with that has been a number of glthread-related improvements to this code that punts executing OpenGL calls to a separate CPU thread. The Zink OpenGL-on-Vulkan driver has now unconditionally enabled OpenGL threading too.
The Vulkan Working Group has released the VK_EXT_mesh_shader extension that brings cross-vendor mesh shading to Vulkan and improves functional compatibility with DirectX 12. The new mesh shading pipeline with the task and mesh shading stages provides an alternative to the traditional vertex, tessellation, or geometry shader stages that feed into rasterization. Mesh shaders provide greater flexibility to developers and enable a two-stage approach for efficient culling, level-of-detail management, and procedural generation of geometry. Compared to the traditional pipeline, mesh shaders enable easy access to the topology of generated primitives and developers are free to repurpose shader threads to perform both vertex shading and primitive shading workloads. Khronos will provide a mesh shader open-source sample to support and showcase the new VK_EXT_mesh_shader extension, and an updated shaderc library in the Vulkan SDK is coming soon. For those that wish to try out the new mesh shader on their own GPU; NVIDIA is shipping the new extension in their beta Vulkan drivers today, and experimental support in the open source RADV and ANV drivers are now available. For additional information developers are invited to: Read the deep-dive blog post Mesh Shading for Vulkan. Attend the free Vulkanised Webinar: ‘Cross-Vendor Mesh Shading with Vulkan’ on Wednesday September 28 . Learn More and Register
For the past couple of years, the Raspberry Pi foundation has been working with Igalia to bring Vulkan to the Raspberry Pi 4 platform. Yesterday, they announced that they have achieved Vulkan 1.2 conformance for the Raspberry Pi 4 Model B along with support for various other extensions, bug fixes and performance improvements.
Khronos has released three new samples for Vulkan. They include: Usage of the VK_EXT_conditional_rendering extension for conditionally toggling the visibility of sub-meshes of a complex glTF model. View Sample A transcoded version of the API sample Terrain Tessellation that illustrates the usage of the C++ bindings of vulkan provided by vulkan.hpp. View Sample A transcoded version of the API sample Compute N-Body that illustrates the usage of the C++ bindings of vulkan provided by vulkan.hpp. View Sample
Imagination Technologies and The Khronos Group are holding the Khronos and Imagination Seminar in Shanghai, a developer event highlighting the rapidly evolving software-hardware ecosystem and the opportunities for GPU technology, open-source standards and open API interfaces across mobile gaming, automotive and cloud. Watch the Khronos and Imagination Seminar on-demand sessions and find out more about the PowerVR SDK. Learn more about Imagination Technologies and the Khronos Group.
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.
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.