SDK tagged news

VRWorks 3.0 Graphics SDK has OpenGL Examples for TuringNVIDIA has released the new VRWorks Graphics SDK V3.0 for application and headset developers along with the NVIDIA display driver 411.63, both updated for NVIDIA's new Turing GPU generation. The drivers are available for download and the SDK has been posted. The SDK includes an OpenGL sample to demonstrate Turing's “Variable Rate Shading” (VRS) feature showing how to vary fragment load across the screen, e.g. for foveated rendering. Another sample demonstrates Turing's “Multi-View Rendering” (MVR) feature by showing how to render the same scene from different viewpoints. There are Vulkan versions of the samples too.

LunarG has released new Vulkan SDKs for Windows, Linux, and macOS based on the 1.1.77 header. Changes and additions to Vulkan SDK 1.1.77 include: Linux SDK is now packaged as a tar.gz file instead of a .run file; Many bug fixes, increased validation coverage and accuracy improvements, and feature additions and new extensions for this SDK release: VK_KHR_get_display_properties2 and VK_KHR_draw_indirect_count.

Enterprises should find it easier to tap the benefits of FPGAs now that Dell EMC and Fujitsu are putting Intel Arria 10 GX Programmable Acceleration Cards into off-the-shelf servers for the data center. The Arria 10 GX cards offers the Intel FPGA SDK for OpenCL to help ease programming hurdles. Xilinx has also been building up the software stack for its own FPGA product families, and recently announced what it calls a new category of programmable chip – the Adaptive Compute Acceleration Platform (ACAP). It says that developers can work with ACAPS using standard tools like C/C++, OpenCL, and Python.

LunarG creates tools to help simplify Vulkan development. We leveraged the new Vulkan Layer Factory to create the Vulkan Assistant Layer, a layer that helps developers identify Vulkan best practices. The Vulkan Assistant Layer — VK_LAYER_LUNARG_assistant_layer — functions as a Vulkan best practices layer and is intended to highlight potential performance issues, questionable usage patterns, common mistakes, and items that may lead to application problems that are not specifically prohibited by the Vulkan specification. The Vulkan Assistant Layer can be found as part of the LunarG Vulkan SDK.

Starting with the next major SDK release (1.0.49.0), the valid usage identification numbers will be changed to accommodate the official valid usage ID management process. If yo are currently using these IDs to filter messages or for debugging purposes, you will need to remap. For more details read the LunarG SDK Release Notes (Linux, Windows) for 1.0.49.0.

The Intel Computer Vision SDK Beta is for developing and deploying vision-oriented solutions on platforms from Intel, including autonomous vehicles, digital surveillance cameras, robotics, and mixed-reality headsets. Based on OpenVX, this SDK offers many useful extensions and supports heterogeneous execution across CPU and SoC accelerators using an advanced graph compiler, optimized and developer-created kernels, and design and analysis tools. It also includes deep-learning tools that unleash inference performance on deep-learning deployment. If the functionality you need is not already available in the supplied library, you can create custom kernels using C, C++, or OpenCL kernels.

The ARM team has updated the Vulkan SDK with new sample code and tutorials. All sample code is released in github, under an MIT license. This latest SDK update includes two new Vulkan features, Vulkan Multipass and Adaptative Scalable Texture Compression, with ARM Mali sample code and tutorials.

NVIDIA has released the new VRWorks SDK for application and headset developers along with the GeForce driver version 378.78. This release includes added samples demonstrating the following new functionality under Vulkan. Vulkan extensions for VR SLI, Single Pass Stereo and Lens Matched Shading are currently released in experimental form and should not be used in production code. Complete details at NVIDIA GameWorks.

Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). The test took place in Nanjing City, China, where ZTE’s engineers used Intel’s midrange Arria 10 FPGA for a cloud inferencing application using a CNN algorithm. The benchmark was achieved on a server holding 4S Intel Xeon E5-2670v3 processors running at 2.30GHz, 128GB DDR4; Intel PSG Arria 10 FPGA Development Kit with one 10AGX115 FPGA, 4GB DDR4 SODIMM, Intel Quartus Prime and OpenCL SDK v16.1. Besides the impressive increase in performance, the team at the ZTE Wireless Institute sped design time with the use of the OpenCL programming language.

LunarG has updated their site to include Vulkan headers for v1.0.39.0. This release contains updates to the loader, parameter validation, and docs for the following extensions: • VK_KHR_get_physical_device_properties2
• VK_KHR_maintenance1
• VK_KHR_shader_draw_parameters
• VK_EXT_direct_mode_display
• VK_EXT_display_surface_counter
• VK_EXT_display_control

The LoaderAndLayerInterface document has been updated and reorganized for ease of use.