DOCSLIB.ORG

Khronos SIGGRAPH Asia Macau Dec16

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Khronos SIGGRAPH Asia Macau Dec16 NNEF New! Neural Net Exchange Format Khronos VR Initiative! Graphics, Compute and Vision APIs Including Vulkan Next Generation GPU Acceleration SIGGRAPH Asia 2016, Macau Neil Trevett Vice President Developer Ecosystem, NVIDIA | President, Khronos [email protected] | @neilt3d November 2016 © Copyright Khronos Group 2016 - Page 1 Khronos Mission Software Silicon Khronos is an International Industry Consortium of over 100 companies creating royalty-free, open standard APIs to enable software to access hardware acceleration for 3D graphics, parallel computing and vision processing © Copyright Khronos Group 2016 - Page 2 Khronos Standards 3D for the Web - JavaScript API for 3D Graphics - Transmission of 3D runtime assets New! Khronos VR Initiative! NNEF Vision / Camera - Tracking and positioning - Scene Analysis 3D Graphics - Games and Virtual Reality - Augmented Reality - CG Effects Parallel Computation - Product Design - Machine Learning - Safety Critical - Scene Comprehension - 3D scene model construction - Video Transcoding © Copyright Khronos Group 2016 - Page 3 OpenCL – Low-level Parallel Programing • Low level programming of heterogeneous parallel compute resources - One code tree can be executed on CPUs, GPUs, DSPs and FPGA • OpenCL C language to write kernel programs to execute on any compute device - Platform Layer API - to query, select and initialize compute devices - Runtime API - to build and execute kernels programs on multiple devices • New in OpenCL 2.2 - OpenCL C++ kernel language - a static subset of C++14 - Adaptable and elegant sharable code – great for building libraries - Templates enable meta-programming for highly adaptive software - Lambdas used to implement nested/dynamic parallelism GPU OpenCL CPU KernelOpenCL Kernel code DSP Runtime API CodeKernelOpenCL compiled for CPU loads and executes CPU CodeKernelOpenCL FPGA CodeKernel devices kernels across devices Devices Code Host © Copyright Khronos Group 2016 - Page 4 OpenCL 2.2 - Top to Bottom C++ Single Source C++ Programming Full support for features in C++14-based Kernel Language API and Language Specs Brings C++14-based Kernel Language into core specification OpenCL C++ Kernel Language SPIR-V 1.1 with C++ support Portable Kernel Intermediate Language SYCL 2.2 for single source C++ Support for C++14-based kernel language e.g. constructors/destructors SPIR-V in Core Subgroups into core Subgroup query operations Shared Virtual Memory clCloneKernel On-device dispatch Low-latency device Generic Address Space timer queries 3-component vectors Enhanced Image Support Device partitioning Additional image formats C11 Atomics Separate compilation and linking Multiple hosts and devices Pipes Enhanced image support Buffer region operations Android ICD Built-in kernels / custom devices Enhanced event-driven execution Enhanced DX and OpenGL Interop Additional OpenCL C built-ins Improved OpenGL data/event interop Dec08 18 months Jun10 18 months Nov11 24 months Nov13 24 months Nov15 7months May16 OpenCL 1.0 OpenCL 1.1 OpenCL 1.2 OpenCL 2.0 OpenCL 2.1 OpenCL 2.2 Specification Specification Specification Specification Specification PROVISIONAL © Copyright Khronos Group 2016 - Page 5 SPIR-V Transforms the Language Ecosystem • First multi-API, intermediate language for parallel compute and graphics - Natively represents structures in shader and kernel languages - https://www.khronos.org/registry/spir-v/papers/WhitePaper.pdf Diverse Languages and Frameworks Multiple Developer Advantages Use same front-end compiler for all platforms Standard Ship SPIR-V – not shader source code Tools for Portable Simpler and more reliable drivers analysis and optimization Reduces runtime kernel compilation time Intermediate Representation Hardware runtimes on multiple architectures © Copyright Khronos Group 2016 - Page 6 Third party kernel and SPIR-V Ecosystem shader Languages Khronos has open sourced ‘glslang’ GLSL to these tools and translators HLSL GLSL SPIR-V compiler Khronos plans to open source these tools soon OpenCL C OpenCL C++ https://github.com/KhronosGroup/SPIRV-Tools SPIR-V (Dis)Assembler LLVM to SPIR-V Bi-directional Translator SPIR-V Validator LLVM Other SPIR-V Intermediate • Khronos defined and controlled Forms cross-API intermediate language • Native support for graphics and parallel constructs • 32-bit Word Stream • Extensible and easily parsed • Retains data object and control IHV Driver ARB_gl_spirv flow information for effective Runtimes extension code generation and translation © Copyright Khronos Group 2016 - Page 7 SYCL for OpenCL • Single-source heterogeneous programming using STANDARD C++ - Use C++ templates and lambda functions for host & device code • Aligns the hardware acceleration of OpenCL with direction of the C++ standard - C++14 with open source C++17 Parallel STL hosted by Khronos Developer Choice The development of the two specifications are aligned so code can be easily shared between the two approaches C++ Kernel Language Single-source C++ Low Level Control Programmer Familiarity ‘GPGPU’-style separation of Approach also taken by device-side kernel source C++ AMP and OpenMP code and host code © Copyright Khronos Group 2016 - Page 8 OpenCV OpenCV Transparent API for OpenCL Kernel Offload • One OpenCL queue per CPU thread • Extensive and widely used open source • CPU threads can share a device vision library - written in optimized C/C++ • OpenCL kernels are executed asynchronously - Free-use BSD license • C++, C, Python and Java interfaces OpenCV Application - Windows, Linux, Mac OS, iOS and Android • Increasingly taking advantage of heterogeneous processing using OpenCL CPU CPU … CPU - OpenCV 3.X Transparent API; Thread Thread Thread single API entry for each function/algorithm - Dynamically loads OpenCL runtime if available; otherwise falls back to CPU code ocl::Queue ocl::Queue … ocl::Queue - Runtime Dispatching; no recompilation! ocl::Device … ocl::Device ocl::Context © Copyright Khronos Group 2016 - Page 9 OpenCL Conformant Implementations 1.0 | May09 1.1 | Jul11 1.2 | Jun12 1.0 | Aug09 1.1 | Aug10 1.2 | May12 2.0 | Dec14 1.0 | May10 1.1 | Feb11 Desktop 1.1 |Mar11 1.2 | Dec12 2.0 | Jul14 2.1 | Jun15 1.0 | May09 1.1 | Jun10 1.2 | May15 1.1 | Aug12 1.2 | Mar16 1.0 | Feb11 1.2 | Sep13 Mobile 1.1 | Nov12 1.2 | Apr14 2.0 | Nov15 1.1 | Apr12 1.2 | Dec14 1.2 | Sep14 1.1 | May13 1.0 | Jan10 Embedded 1.2 | May15 1.2 | Aug15 1.0 | Jul13 FPGA 1.0 | Dec14 Vendor timelines are Dec08 Jun10 Nov11 Nov13 Nov15 first implementation of OpenCL 1.0 OpenCL 1.1 OpenCL 1.2 OpenCL 2.0 OpenCL 2.1 each spec generation Specification Specification Specification Specification Specification © Copyright Khronos Group 2016 - Page 10 OpenCL Roadmap DISCUSSION • Thin, powerful, explicit run-time for control and predictability • Feature sets and dial-able precision for target market agility • Installable tools and three layer ecosystem for flexibility Applications Vendor-supplied and Math Language Tool open source middleware Libraries Front-ends Layers API Definitions Dial-able types Thin, explicit run-time with rigorous Real-time Pre- Explicit Self-synchronized, Stream and precision memory/execution model. emption and Asynch self-scheduled Processing … QoS scheduling DMA graphs Installable tool & Low-latency, fine-grain pre-emption validation layers and synchronization Features that can be enabled for particular target markets © Copyright Khronos Group 2016 - Page 11 Khronos Standards 3D for the Web - JavaScript API for 3D Graphics - Transmission of 3D runtime assets New! Khronos VR Initiative! NNEF Vision / Camera - Tracking and positioning - Scene Analysis 3D Graphics - Games and Virtual Reality - Augmented Reality - CG Effects Parallel Computation - Product Design - Machine Learning - Safety Critical - Scene Comprehension - 3D scene model construction - Video Transcoding © Copyright Khronos Group 2016 - Page 12 The Need for a New Generation GPU API • Explicit - Direct GPU control, predictable - no driver surprises • Faster - Reduce CPU overhead and latency, multi-thread scaling • Portable - Efficient on cloud, desktop, console, mobile and embedded OpenGL has evolved over 25 years and GPUs are increasingly programmable and GPUs will accelerate graphics, compute, vision continues to meet industry needs – but there is compute capable + platforms are becoming and deep learning across diverse platforms: a need for a complementary API approach mobile, memory-unified and multi-core FLEXIBILITY and PORTABILITY are key © Copyright Khronos Group 2016 - Page 13 Three New Generation GPU APIs Only Windows 10 Only Apple Cross Platform N Vulkan is extensible – just like OpenGL - and so is the new only generation API where hardware vendors can deliver innovations to market whenever they need © Copyright Khronos Group 2016 - Page 14 The Key Principle of Vulkan: Explicit Control • Application tells the driver what it is going to do You have to supply a LOT of information! - In enough detail that driver doesn’t have to guess - When the driver needs to know it And, you have to supply it early • In return, driver promises to do - What the application asks for - When it asks for it - Very quickly Efficient, predictable performance • No driver magic – no surprises © Copyright Khronos Group 2016 - Page 15 Vulkan - No Compromise Performance Potential Performance Gain ‘Half Way New Gen’ Retains Traditional Binding Model Mixes OpenGL ES 3.1/OpenCL 1.2 C++11-based kernel language Bindings to Objective-C and Swift Amount of work to port (missing functionality such as Geometry Shaders) from traditional
Load more

Recommended publications
  • The State of Vulkan on Apple 03June 2021
    The State of Vulkan on Apple Devices Why you should be developing for the Apple ecosystem with Vulkan, and how to do it. Richard S. Wright Jr., LunarG June 3, 2021 If you are reading this, you likely already know what Vulkan is -- a low-overhead, high-performance, cross-platform, graphics and compute API designed to take maximum advantage of today's highly parallel and scalable graphics and compute hardware. To be sure, there are other APIs with this goal such as Microsoft’s DirectX and Apple’s Metal API. For a long time OpenGL matured to meet the needs of rapidly evolving hardware and met well the challenges of cross-platform development of high-performance graphics applications. OpenGL will remain viable for a very long time for many applications (and can actually be layered on top of Vulkan), but to take maximum advantage of modern hardware, a new and somewhat reinvented approach is called for. Everyone does not need the level of control that Vulkan provides, but if you do, you can think of Vulkan as a lower-level successor to OpenGL in that it attempts to enable highly portable, yet high-performance, application development across desktop and mobile device platforms. Writing platform specific code does have its advantages, and vendors such as Microsoft and Apple certainly adore having best of breed titles available exclusively for their customers as it adds value to their ecosystem. For developers though, it is often in our best interests to make our products available as widely as possible. Aside from gaming consoles with their mostly closed development environments, Windows, Linux, Apple, and Android combined represent most of the market for developers of end user software and games today.
    [Show full text]
  • GRAPHICS PROGRAMMING THEN and NOW How the Ways of Showing Pixels on Screen Have Changed
    Aatu Mikkonen GRAPHICS PROGRAMMING THEN AND NOW How the ways of showing pixels on screen have changed GRAPHICS PROGRAMMING THEN AND NOW How the ways of showing pixels on screen have changed Aatu Mikkonen Bachelor’s Thesis Spring 2021 Bachelor’s Degree of Information Tech- nology Oulu University of Applied Sciences ABSTRACT Oulu University of Applied Sciences Bachelor’s degree of Information technology Author(s): Aatu Mikkonen Title of the thesis: Graphics Programming Then and Now Thesis examiner(s): Kari Laitinen Term and year of thesis completion: Spring 2021 Pages: 20 Graphics programming is relatively unknown form of programming even though everyone uses its capabilities every day, e.g., writing documents, creating art on a computer and playing or creating video games. Graphics programming, at least in Finland, does not have much literature written for it. The purpose of this report is to examine how the graphics programming has evolved from the old times to modern times, and examine how the tools for writing graphics programming has changed. The author applied background knowledge learned in school and in free time about the research. The work was carried out by using the internet with search engines and online documentation searches. A variety of books, videos, articles and documentation pages were used as materials. The main results are a brief overview on the differences in graphics programming from the old times to modern times, descriptions on the areas graphics programming handles and a small example on the implementation of graphics program. Keywords: graphics, graphics programming, graphics history, api CONTENTS TERMINOLOGY AND ABBREVIATIONS .....................................................................................
    [Show full text]
  • KHRONOS GROUP Update to Web3d
    Update to Web3D Los Angeles, July 2019 Neil Trevett Khronos President NVIDIA VP Developer Ecosystems [email protected] | @neilt3d ® © Khronos Group 2019 © Khronos® Group Inc. 2019 - Page 1 Active Khronos Standards 3D Commerce Working Group Announced at SIGGRAPH! Khronos is an open, member-driven industry consortium developing royalty-free standards, to harness the power of silicon acceleration for demanding graphics rendering and computationally intensive applications © Khronos® Group Inc. 2019 - Page 2 Vulkan Explicit GPU Control Simpler drivers - application has the best knowledge for holistic optimization – no ‘driver magic’ Complex drivers Application cause overhead Single thread per context Explicit creation of API objects and inconsistent Application before usage – efficient, behavior across Memory allocation Multiple Front-end predictable execution vendors Thread management Explicit Synchronization Compilers Easier portability - no fighting High-level Driver GLSL, HLSL etc. Always active Multi-threaded generation with different vendor heuristics of command buffers error handling Abstraction Layered GPU Control Validation and debug layers Full GLSL Context management SPIR-V loaded only when needed preprocessor and Memory allocation pre-compiled shaders compiler in Full GLSL compiler SPIR-V intermediate language: Error detection driver Thin Driver Loadable debug and shading language flexibility Explicit GPU Control validation layers OpenGL vs. Unified API across mobile and OpenGL ES desktop platforms GPU GPU Multiple graphics, command and DMA queues A Graphics API A GPU API © Khronos® Group Inc. 2019 - Page 3 Pervasive Vulkan Major GPU Companies supporting Vulkan for Desktop and Mobile Platforms http://vulkan.gpuinfo.org/ Platforms Consoles Desktop Mobile (Android 7.0+) Media Players Virtual Reality Cloud Services Game Streaming Embedded Game Engines Croteam Serious Engine © Khronos® Group Inc.
    [Show full text]
  • Release V0.1-Alpha.3 Inexor Collective
    Inexor Vulkan Renderer Release v0.1-alpha.3 Inexor Collective Sep 29, 2021 CONTENTS 1 Documentation 3 1.1 Development...............................................3 1.2 Source Code............................................... 57 1.3 How to contribute............................................ 162 1.4 Frequently asked questions........................................ 167 1.5 Changelog................................................ 172 1.6 Helpful Links............................................... 174 1.7 Source Code License........................................... 177 1.8 Contact us................................................ 177 1.9 Frequently asked questions........................................ 178 Index 185 i ii Inexor Vulkan Renderer, Release v0.1-alpha.3 Inexor is a MIT-licensed open-source project which develops a new 3D octree game engine by combining modern C++ with Vulkan API. CONTENTS 1 Inexor Vulkan Renderer, Release v0.1-alpha.3 2 CONTENTS CHAPTER ONE DOCUMENTATION Quickstart: Building Instructions (Windows/Linux)& Getting started 1.1 Development 1.1.1 Supported platforms • Vulkan API is completely platform-agnostic, which allows it to run on various operating systems. • The required drivers for Vulkan are usually part of your graphic card’s drivers. • Update your graphics drivers as often as possible since new drivers with Vulkan updates are released frequently. • Driver updates contain new features, bug fixes, and performance improvements. • Check out Khronos website for more information. Microsoft Windows • We support x64 Microsoft Windows 8, 8.1 and 10. • We have build instructions for Windows. Linux • We support every x64 Linux distribution for which Vulkan drivers exist. • We have specific build instructions for Gentoo and Ubuntu. • If you have found a way to set it up for other Linux distributions, please open a pull request and let us know! macOS and iOS • We do not support macOS or iOS because it would require us to use MoltenVK to get Vulkan running on Mac OS.
    [Show full text]
  • Compute Shader in Image Processing Development∗
    Compute Shader in Image Processing Development∗ Robert Tornai, Péter Fürjes-Benke University of Debrecen, Faculty of Informatics [email protected] [email protected] Proceedings of the 1st Conference on Information Technology and Data Science Debrecen, Hungary, November 6–8, 2020 published at http://ceur-ws.org Abstract This paper will present the OpenGL compute shader implementation of the BlackRoom software. BlackRoom is a platform-independent image pro- cessing program, which supports multiple execution branches like Vulkan fragment shader, OpenGL fragment shader, and CPU-based rendering. In order to support a wider range of devices with different amounts of mem- ory, users can utilize tile rendering, and the program can be run in browsers thanks to the WebAssembly format. Thanks to our program’s built-in benchmark system, the performance dif- ferences between the implemented CPU- and GPU-based executing branches can be easily determined. We made a comprehensive comparison between the rendering performance of our CPU, OpenGL compute shader, fragment shader and Vulkan fragment shader branches. Latter is under development, which induces a relatively higher runtime presently. A further aim is to optimize our algorithms, which are using Vulkan API. Besides that, the program will be capable of rendering multiple effects at once with Vulkan fragment shader. Furthermore, the available GPU rendering and multi-threading features are planned to be enabled for WebAssembly platform yielded by the Qt framework [2]. Keywords: Image processing, benchmark, CPU, shaders, Vulkan, OpenGL AMS Subject Classification: 65D18, 68U10, 97R60 Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
    [Show full text]
  • Putting Randomized Compiler Testing Into Production
    1 Putting Randomized Compiler Testing into 2 Production 3 Alastair F. Donaldson 4 Google, UK 5 Imperial College London, UK 6 [email protected] 7 Hugues Evrard 8 Google, UK 9 [email protected] 10 Paul Thomson 11 Google, UK 12 [email protected] 13 Abstract 14 We describe our experience over the last 18 months on a compiler testing technology transfer project: 15 taking the GraphicsFuzz research project on randomized metamorphic testing of graphics shader 16 compilers, and building the necessary tooling around it to provide a highly automated process 17 for improving the Khronos Vulkan Conformance Test Suite (CTS) with test cases that expose 18 fuzzer-found compiler bugs, or that plug gaps in test coverage. We present this tooling for test 19 automation—gfauto—in detail, as well as our use of differential coverage and test case reduction 20 as a method for automatically synthesizing tests that fill coverage gaps. We explain the value 21 that GraphicsFuzz has provided in automatically testing the ecosystem of tools for transforming, 22 optimizing and validating Vulkan shaders, and the challenges faced when testing a tool ecosystem 23 rather than a single tool. We discuss practical issues associated with putting automated metamorphic 24 testing into production, related to test case validity, bug de-duplication and floating-point precision, 25 and and provide illustrative examples of bugs found during our work. 26 2012 ACM Subject Classification Software and its engineering → Compilers; Software and its 27 engineering → Software testing and debugging 28 Keywords and phrases Compilers, metamorphic testing, 3D graphics, experience report 29 Digital Object Identifier 10.4230/LIPIcs.ECOOP.2020.22 30 Category Experience Report 31 1 Introduction 32 Graphics processing units (GPUs) provide hardware-accelerated graphics in many scenarios, 33 such as 3D and 2D games, applications, web browsers, and operating system user interfaces.
    [Show full text]
  • Vulkan Api Download Android Vulkan Api Download Android
    vulkan api download android Vulkan api download android. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Cloudflare Ray ID: 66cc6b9488dfc433 • Your IP : 188.246.226.140 • Performance & security by Cloudflare. Vulkan api download android. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware. If you are at an office or shared network, you can ask the network administrator to run a scan across the network looking for misconfigured or infected devices. Another way to prevent getting this page in the future is to use Privacy Pass. You may need to download version 2.0 now from the Chrome Web Store. Cloudflare Ray ID: 66cc6b948d6f84d4 • Your IP : 188.246.226.140 • Performance & security by Cloudflare. Vulkan api download android. Completing the CAPTCHA proves you are a human and gives you temporary access to the web property. What can I do to prevent this in the future? If you are on a personal connection, like at home, you can run an anti-virus scan on your device to make sure it is not infected with malware.
    [Show full text]
  • Evulkan; a Vulkan Graphics Library
    Bournemouth University National Centre for Computer Animation MSc in Computer Animation and Visual Effects evulkan A Vulkan Graphics Library Eimear Crotty github.com/eimearc/masters August 2020 Abstract Vulkan is a low-level graphics and compute API which aims to provide users with faster draw speeds by removing overhead from the driver. The user is expected to explicitly provide the details previously generated by the driver. The resulting extra code can be difficult to understand and taxing to write for beginners, leading to the need for a helper library. i Acknowledgements Thanks to Jon Macey for his help on the C++ side of things and for loaning me his Vulkan book. Many thanks to my uncle Neil for giving me a second home during the year. Those curries and trips to the Glasshouse kept me going through multiple challenging assign- ments. I’m sorry they were cut short. Finally, thanks to my mum Kerry, dad Owen, siblings Rory, Aisling, Aoife and Ellie for their support during the last year. ii Contents 1 Introduction1 2 Previous Work2 2.1 V-EZ....................................2 2.2 Anvil....................................2 2.3 GLOVE...................................2 2.4 MoltenVK.................................3 2.5 Personal Inquiry..............................3 3 Technical Background4 3.1 Useful Resources..............................4 3.2 Comparison with OpenGL.........................4 3.3 Vulkan Layers...............................5 3.3.1 Loader...............................5 3.3.2 Dispatch Chains..........................6 3.4 Vulkan Components............................7 3.4.1 VkInstance.............................7 3.4.2 VkPhysicalDevice.........................8 3.4.3 VkDevice..............................8 3.4.4 VkQueue..............................8 3.4.5 VkDeviceMemory.........................8 3.4.6 VkCommandBuffer.........................9 3.4.7 VkSwapchainKHR.........................9 3.5 Vulkan Object Model..........................
    [Show full text]
  • Vulkan Tutorial
    Vulkan Tutorial Alexander Overvoorde April 2020 Contents Introduction 7 About .................................... 7 E-book .................................... 8 Tutorial structure .............................. 8 Overview 10 Origin of Vulkan .............................. 10 What it takes to draw a triangle ..................... 11 Step 1 - Instance and physical device selection ........... 11 Step 2 - Logical device and queue families ............. 11 Step 3 - Window surface and swap chain .............. 11 Step 4 - Image views and framebuffers ............... 12 Step 5 - Render passes ........................ 12 Step 6 - Graphics pipeline ...................... 13 Step 7 - Command pools and command buffers .......... 13 Step 8 - Main loop .......................... 13 Summary ............................... 14 API concepts ................................ 15 Coding conventions .......................... 15 Validation layers ........................... 15 Development environment 17 Windows .................................. 17 Vulkan SDK .............................. 17 GLFW ................................. 19 GLM .................................. 19 Setting up Visual Studio ....................... 20 Linux .................................... 27 Vulkan SDK .............................. 27 GLFW ................................. 29 GLM .................................. 29 Setting up a makefile project .................... 29 MacOS ................................... 33 Vulkan SDK .............................. 33 1 GLFW ................................
    [Show full text]
  • Interoperable GPU Kernels As Latency Improver for MEC
    Interoperable GPU Kernels as Latency Improver for MEC Juuso Haavisto, and Jukka Riekki Center for Ubiquitous Computing, University of Oulu Email: [email protected] Abstract—Mixed reality (MR) applications are expected to Due to the lack of such empirical research, we hereby present become common when 5G goes mainstream. However, the latency such in this paper: we demonstrate an approach that addresses requirements are challenging to meet due to the resources the end-to-end (E2E) latency between the MEC server and the required by video-based remoting of graphics, that is, decoding video codecs. We propose an approach towards tackling this chal- mobile UE. lenge: a client-server implementation for transacting intermediate For MR applications, MECs can be used to create graphcis representation (IR) between a mobile UE and a MEC server for UEs. In general, our method to reduce latency questions instead of video codecs and this way avoiding video decoding. We whether MEC applications should remote graphics via video demonstrate the ability to address latency bottlenecks on edge codecs, as the current cloud computing equivalents do [1]. computing workloads that transact graphics. We select SPIR- V compatible GPU kernels as the intermediate representation. While these video streaming services, such as Google Stadia, Our approach requires know-how in GPU architecture and GPU work with home-network fiber connections, previous studies domain-specific languages (DSLs), but compared to video-based [2] show mobile UEs having a latency problem with video edge graphics, it decreases UE device delay by sevenfold. Further, codec decoding. Here, the UE must decode and render video we find that due to low cold-start times on both UEs and MEC frames while maintaining a low-latency and reliable cellular servers, application migration can happen in milliseconds.
    [Show full text]
  • Khronos Template 2015
    Standards update and liaison report January 2019 Original Slides are written by Neil Trevett | Khronos President Modified and Presented by Hwanyong Lee | Khronos Liaison Representative www.khronos.org © Copyright Khronos™ Group 2018 - Page 1 PROMOTER MEMBERS Over 140 members worldwide Any company is welcome to join © Copyright Khronos™ Group 2018 - Page 2 Topics • OpenXR first public demonstrations - StarVR and Microsoft Windows Mixed Reality headsets • NNEF 1.0 released at SIGGRAPH - Neural Network Exchange Format for machine learning • Khronos Educators Program launch - Shared creation and refinement of course materials • 3D API ecosystem progress - Vulkan 1.1, OpenGL 4.6, OpenGL ES 3.2, WebGL 2.0 - Porting Vulkan apps to closed platforms • glTF Widespread Industry Adoption - Working on Texture Transmission extension • Liaison Report © Copyright Khronos™ Group 2018 - Page 3 OpenXR – Solving VR Fragmentation VR VR VR VR VR VR VR VR App App App App App App App App 1 2 3 4 1 2 3 4 Proprietary Proprietary Engine Engine Application Interface Device Layer VR VR VR VR VR VR VR VR VR VR Device Device Device Device Device Device Device Device Device Device 1 2 3 4 5 1 2 3 4 5 Before OpenXR After OpenXR VR Market Wide interoperabilityof Fragmentation VR apps and devices © Copyright Khronos™ Group 2018 - Page 4 Companies Publicly Supporting OpenXR OpenXR is a collaborative design 1) For cross-platform XR portability – VR in V1.0, then add AR 2) Integrating many lessons from proprietary ‘first-generation’ API designs © Copyright Khronos™ Group
    [Show full text]
  • Gstreamer Vulkan
    GStreamer Vulkan Matthew Waters (ystreet00) GStreamer Conference 2019 1st November 2019 Who Am I ● Australian ● Centricular ● Multimedia ● Graphics – OpenGL, Vulkan ● WebRTC 2 History 3 Why Vulkan/Metal/Direct3D 12? https://www.karlrupp.net/2018/02/42-years-of-microprocessor-trend-data/ - CC BY 4.0 4 Why Vulkan/Metal/Direct3D 12? ● Multi-core processing ● Lower GPU driver overhead ● Closer to current state of GPU hardware ● API ‘reset’ 5 Hello Triangle https://twitter.com/Sol_HSA/status/1181459830361509888 6 https://twitter.com/McNopper/status/1179774428357505024 7 Why Vulkan? ● Open cross-platform low-level 3D API ● X11, Wayland, Android, Windows, Embedded Linux ● MacOS/iOS with MoltenVK – OpenGL deprecated on MacOS/iOS ● Extensible ● Lots of control 8 Vulkan Overview Instance Physical Device Device Descriptor Pool Semaphore Sampler Memory Queue Buffer Fence Heap Render Pass Framebuffer Shader Image Pipeline Command Command Descriptor Pool Buffer(s) Set 9 Vulkan Extensions ● Chosen by application at instance/device creation – Explicitly opt-in ● Rendering output is an extension – VK_KHR_SURFACE + platform-specific extension 10 Vulkan Command Buffers Instance Physical Device Device Queue Command Pool Command Buffer Render Pass Bind Index/ Set Viewport/ Bind Render BindPipeline Draw Begin Vertex Buffer Scissor... Descriptor Set Pass End Render Pass State Descriptor Shaders Set Framebuffer Buffer Render Pass etc... Descriptor Image View Pool Image Memory Heap Sampler 11 Vulkan Synchronisation ● Semaphores – device→device inter-queue or coarse
    [Show full text]