News Archives

The second Release Candidate (RC) milestone of the upcoming Mesa 3D 13.0.0 Graphics Library has been announced. Changes implemented in Mesa 13.0.0 RC2 include the move of the BlendBarrier and PrimitiveBoundingBox definitions into the ES3.2 category for GLAPI, export of all GLES (OpenGL ES) 3.2 functions in the libGLESv2.so library, and the set of the VISIBILITY_CFLAGS argument for shared GLAPI to the automake file the MAPI generic OpenVG dispatcher.

Vulkan API supports multithreading, which is particularly important for mobile platforms. Multithreading enables the system to balance the workload across multiple CPUs, allowing for lower voltage and frequency. The results give considerable energy savings compared to OpenGL ES API. In this video from ARM, you can see just how big a difference there is between OpenGL ES and Vulkan.

This webinar examines both the graphical and video content needed to drive the adoption of VR. The widespread uptake of VR will depend on the creation of compelling use cases for the consumer. We will focus on two main use cases today, immersive 360 degree video content creation and display, and high quality gaming.
What will you learn?
• How to create compelling 3D GFX content for VR applications
• Khronos APIs and extensions for VR graphics
• 360° video creation – encoding, stitching and playback

1NVIDIA demonstrated at GTC Europe a high-end virtual reality demo of a complete car model. You can explore every detail of the complete car model in virtual reality. To accomplish this, the demo harnesses the NV_gpu_multicast OpenGL extension so two Quadro P6000 can render the left- and right-eye views in parallel and then handles the massive geometric detail with the NV_command_list OpenGL extension.

The Khronos Group today announced the creation of two standardization initiatives to address the growing industry interest in the deployment and acceleration of neural network technology. Firstly, Khronos has formed a new working group to create an API independent standard file format for exchanging deep learning data between training systems and inference engines. Work on generating requirements and detailed design proposals for the Neural Network Exchange Format (NNEF™) is already underway, and companies interested in participating are welcome to join Khronos for a voice and a vote in the development process. Secondly, the OpenVX™ working group has released an extension to enable Convolutional Neural Network topologies to be represented as OpenVX graphs and mixed with traditional vision functions. Read the press release about both of these Neural Network Standard Initiatives.