모바일 GPU 동향 Trends of Mobile GPU 임베디드 소프트웨어 & 시스템반도체 기술 특집
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Download Speeds Performance and Optimized for Long Battery Life
® QUALCOMM FEATURING THE LATEST IN MOBILE TECHNOLOGY. TM SNAPDRAGON Capture sharper, higher-quality images, in challenging lighting situations Qualcomm’s Spectra 14-bit dual image signal processors tap into the enhanced performance and feature enhancements that Hexagon 680 DSP’s HVX 820MOBILE PROCESSOR performance adds with amazing features like Low Light Photo and Video and Touch-to-Track where ISP and DSP work intelligently together to enhance imaging as well as track movements and improve zoom. Enabling a more immersive, intuitive and Immersive, life-like connected experience. virtual reality The Snapdragon 820 mobile processor Experience realistic, visual and audio immersion and offers many advantages: smooth VR action enabled by Snapdragon 820’s • New X12 LTE: Industry leading Heterogeneous compute platform, designed for high connectivity with LTE download speeds performance and optimized for long battery life. of up to 600 Mbps and multi-gigabit 802.11ad Wi-Fi • New Qualcomm® Kryo CPU: Delivering Next-generation maximum performance and low power consumption Kryo is QTI’s first custom computer vision 64-bit quad-core CPU, manufactured Drive more safely with object detection and enhanced in advanced 14nm FinFET LPP process navigation and enhance your smartphone camera • New Qualcomm® Adreno 530: Up to capability with features that can track faces and 40% better graphics and compute objects for a more intelligent mobile experience. performance with the Adreno 530 GPU • Qualcomm Spectra™ 14-bit dual image signal processors (ISPs) deliver high Deeply immersive resolution DSLR-quality images using heterogeneous compute for advanced 3D gaming processing and additional power The combination of Snapdragon 820’s Adreno 530 GPU savings and Kryo CPU creates enough compute performance • New Hexagon 680 DSP includes to enable console quality games and exciting, next Hexagon Vector eXtensions and Sensor generation virtual reality applications. -
GPU Developments 2018
GPU Developments 2018 2018 GPU Developments 2018 © Copyright Jon Peddie Research 2019. All rights reserved. Reproduction in whole or in part is prohibited without written permission from Jon Peddie Research. This report is the property of Jon Peddie Research (JPR) and made available to a restricted number of clients only upon these terms and conditions. Agreement not to copy or disclose. This report and all future reports or other materials provided by JPR pursuant to this subscription (collectively, “Reports”) are protected by: (i) federal copyright, pursuant to the Copyright Act of 1976; and (ii) the nondisclosure provisions set forth immediately following. License, exclusive use, and agreement not to disclose. Reports are the trade secret property exclusively of JPR and are made available to a restricted number of clients, for their exclusive use and only upon the following terms and conditions. JPR grants site-wide license to read and utilize the information in the Reports, exclusively to the initial subscriber to the Reports, its subsidiaries, divisions, and employees (collectively, “Subscriber”). The Reports shall, at all times, be treated by Subscriber as proprietary and confidential documents, for internal use only. Subscriber agrees that it will not reproduce for or share any of the material in the Reports (“Material”) with any entity or individual other than Subscriber (“Shared Third Party”) (collectively, “Share” or “Sharing”), without the advance written permission of JPR. Subscriber shall be liable for any breach of this agreement and shall be subject to cancellation of its subscription to Reports. Without limiting this liability, Subscriber shall be liable for any damages suffered by JPR as a result of any Sharing of any Material, without advance written permission of JPR. -
An Evolution of Mobile Graphics
AN EVOLUTION OF MOBILE GRAPHICS Michael C. Shebanow Vice President, Advanced Processor Lab Samsung Electronics July 20, 20131 DISCLAIMER • The views herein are my own • They do not represent Samsung’s vision nor product plans 2 • The Mobile Market • Review of GPU Tech • GPU Efficiency • User Experience • Tech Challenges • Summary 3 The Rise of the Mobile GPU & Connectivity A NEW WORLD COMING? 4 DISCRETE GPU MARKET Flattening 5 MOBILE GPU MARKET Smart • In 2012, an estimated 800+ Phones million mobile GPUs shipped “Phablets” • ~123M tablets • ~712M smart phones Tablets • Will easily exceed 1B in the coming years • Trend: • Discrete GPU relatively flat • Mobile is growing rapidly 6 WW INTERNET TRAFFIC • Source: Cisco VNI Mobile INET IP Traffic growth Traffic • Internet traffic growth Year (TB/sec) rate (TB/sec) rate is staggering 2005 0.9 0.00 2006 1.5 65% 0.00 • 2012 total traffic is 2007 2.5 61% 0.01 13.7 GB per person 2008 3.8 54% 0.01 per month 2009 5.6 45% 0.04 2010 7.8 40% 0.10 • 2012 smart phone 2011 10.6 36% 0.23 traffic at 2012 12.4 17% 0.34 0.342 GB per person per month • 2017 smart phone traffic expected at 2.7 GB per person per month 7 WHERE ARE WE HEADED?… • Enormous quantity of GPUs • Large amount of interconnectivity • Better I/O 8 GPU Pipelines A BRIEF REVIEW OF GPU TECH 9 MOBILE GPU PIPELINE ARCHITECTURES Tile-based immediate mode rendering IA VS CCV RS PS ROP (TBIMR) Tile-based deferred IA VS CCV scene rendering (TBDR) RS PS ROP IA = input assembler VS = vertex shader CCV = cull, clip, viewport transform RS = rasterization, -
CES 2016 Exhibitor Listing As of 1/19/16
CES 2016 Exhibitor Listing as of 1/19/16 Name Booth * Cosmopolitan Vdara Hospitality Suites 1 Esource Technology Co., Ltd. 26724 10 Vins 80642 12 Labs 73846 1Byone Products Inc. 21953 2 the Max Asia Pacific Ltd. 72163 2017 Exhibit Space Selection 81259 3 Legged Thing Ltd 12045 360fly 10417 360-G GmbH 81250 360Heros Inc 26417 3D Fuel 73113 3D Printlife 72323 3D Sound Labs 80442 3D Systems 72721 3D Vision Technologies Limited 6718 3DiVi Company 81532 3Dprintler.com 80655 3DRudder 81631 3Iware Co.,Ltd. 45005 3M 31411 3rd Dimension Industrial 3D Printing 73108 4DCulture Inc. 58005 4DDynamics 35483 4iiii Innovations, Inc. 73623 5V - All In One HC 81151 6SensorLabs BT31 Page 1 of 135 6sensorlabs / Nima 81339 7 Medical 81040 8 Locations Co., Ltd. 70572 8A Inc. 82831 A&A Merchandising Inc. 70567 A&D Medical 73939 A+E Networks Aria 36, Aria 53 AAC Technologies Holdings Inc. Suite 2910 AAMP Global 2809 Aaron Design 82839 Aaudio Imports Suite 30-116 AAUXX 73757 Abalta Technologies Suite 2460 ABC Trading Solution 74939 Abeeway 80463 Absolare USA LLC Suite 29-131 Absolue Creations Suite 30-312 Acadia Technology Inc. 20365 Acapella Audio Arts Suite 30-215 Accedo Palazzo 50707 Accele Electronics 1110 Accell 20322 Accenture Toscana 3804 Accugraphic Sales 82423 Accuphase Laboratory Suite 29-139 ACE CAD Enterprise Co., Ltd 55023 Ace Computers/Ace Digital Home 20318 ACE Marketing Inc. 59025 ACE Marketing Inc. 31622 ACECAD Digital Corp./Hongteli, DBA Solidtek 31814 USA Acelink Technology Co., Ltd. Suite 2660 Acen Co.,Ltd. 44015 Page 2 of 135 Acesonic USA 22039 A-Champs 74967 ACIGI, Fujiiryoki USA/Dr. -
Vivante Corporation Introduction
World’s Smallest OpenGL ES 2.0 Silicon Introduction to Vivante Graphics Processor IP Khronos DevU - December 2009 2009 Silicon Proven in the Marketplace Vivante GPUs to ship in tier one consumer products four key market segments Smart Phone Digital Picture & Frame Mobile MID Gaming Netbook Home Embedded Entertainment 2009 World’s Smallest OpenGL ES 2.0 GPU Technology Leader in GPU IP Delivers 2x Advantages • Most efficient solution • 2x Performance per mm2 • Support 1080HD and higher • 30+ Licensees • Silicon proven in multiple applications 2009 smaller faster cooler 30+ Licensees Vivante Marketplace GC2000 in 65LP 500 MHz 100 Mtri/s 1.0 Gpix/s 18 GFLOPS GC400 in 65LP 2.5 mm2 silicon 49 mW active 13 Mtri/s 125 Mpix/s CAMERA ∗ MOBILE PHONE ∗ NAVIGATION ∗ PRINTER ∗ AUTOMOTIVE ∗ NETBOOK ∗ MID ∗ SET-TOP BOX ∗ HDTV ∗ MOBILE GAMING DTV Digital Smartphone MID Blu-ray Picture Camera GPS Netbook Frame Set-top box 2009 Vivante Differentiation ScalarMorphicTM Architecture GC GPU Core Multiple dimensions of AHB AXI scalability for optimal Host Interface cost/area/power balance Memory Controller Unified shaders Scalable multicore design 3-D Pipeline Texture Hyper-threading virtually Engine Engine 3-D RenderingEngine eliminates latency effects Engine Simple integration Ultra-threaded Unified Shader Ultra-threadedUltra-threaded Unified Unified Shader Shader Low bus bandwidth Graphics Up to 256 threads per Shader Pipeline Pixel Produces a small area, Front Engine high performance End 2-D Pipeline 2-D Drawing and Scaling Engine 2009 Complete Graphics -
The Openvx™ Specification
The OpenVX™ Specification Version 1.0.1 Document Revision: r31169 Generated on Wed May 13 2015 08:41:43 Khronos Vision Working Group Editor: Susheel Gautam Editor: Erik Rainey Copyright ©2014 The Khronos Group Inc. i Copyright ©2014 The Khronos Group Inc. All Rights Reserved. This specification is protected by copyright laws and contains material proprietary to the Khronos Group, Inc. It or any components may not be reproduced, republished, distributed, transmitted, displayed, broadcast or otherwise exploited in any manner without the express prior written permission of Khronos Group. You may use this specifica- tion for implementing the functionality therein, without altering or removing any trademark, copyright or other notice from the specification, but the receipt or possession of this specification does not convey any rights to reproduce, disclose, or distribute its contents, or to manufacture, use, or sell anything that it may describe, in whole or in part. Khronos Group grants express permission to any current Promoter, Contributor or Adopter member of Khronos to copy and redistribute UNMODIFIED versions of this specification in any fashion, provided that NO CHARGE is made for the specification and the latest available update of the specification for any version of the API is used whenever possible. Such distributed specification may be re-formatted AS LONG AS the contents of the specifi- cation are not changed in any way. The specification may be incorporated into a product that is sold as long as such product includes significant independent work developed by the seller. A link to the current version of this specification on the Khronos Group web-site should be included whenever possible with specification distributions. -
The Openvx™ Specification
The OpenVX™ Specification Version 1.2 Document Revision: dba1aa3 Generated on Wed Oct 11 2017 20:00:10 Khronos Vision Working Group Editor: Stephen Ramm Copyright ©2016-2017 The Khronos Group Inc. i Copyright ©2016-2017 The Khronos Group Inc. All Rights Reserved. This specification is protected by copyright laws and contains material proprietary to the Khronos Group, Inc. It or any components may not be reproduced, republished, distributed, transmitted, displayed, broadcast or otherwise exploited in any manner without the express prior written permission of Khronos Group. You may use this specifica- tion for implementing the functionality therein, without altering or removing any trademark, copyright or other notice from the specification, but the receipt or possession of this specification does not convey any rights to reproduce, disclose, or distribute its contents, or to manufacture, use, or sell anything that it may describe, in whole or in part. Khronos Group grants express permission to any current Promoter, Contributor or Adopter member of Khronos to copy and redistribute UNMODIFIED versions of this specification in any fashion, provided that NO CHARGE is made for the specification and the latest available update of the specification for any version of the API is used whenever possible. Such distributed specification may be re-formatted AS LONG AS the contents of the specifi- cation are not changed in any way. The specification may be incorporated into a product that is sold as long as such product includes significant independent work developed by the seller. A link to the current version of this specification on the Khronos Group web-site should be included whenever possible with specification distributions. -
Amd Mobile Gpu
1 / 2 Amd Mobile Gpu The partnership will see Samsung use ultra-low power high-performance mobile graphics IP based on AMD Radeon graphics technologies for .... The power pairing of the new eight-core AMD Ryzen 9 5900HS processor in the laptop and Nvidia GeForce RTX 3080 mobile GPU in the .... AMD says gaming laptops featuring GPUs based on its new RDNA 2 ... To showcase the performance of its mobile GPUs, Su showed off Dirt 5 .... The interesting question is whether the GPU pipeline will evolve to perform more ... AMD's Fusion and Intel's Nehalem projects [1222]. ... However, it seems aimed more at the mobile market, where small size and lower wattage matter more.. I attended several keynotes and press conferences including AMD's CES keynote where they announced its Ryzen 4000 Series Mobile Processors, code-named “ .... The new AMD Radeon Pro 5600M paves the way for desktop-class graphics performance with superb efficiency on mobile computing .... This is all 9XX series Mobile GPUs. 1 external ... Frame Pacing Enhancements for AMD Dual Graphics. Both of ... 60 or newer version of the mobile driver (347.. This points to an AMD GPU inside 2022's Galaxy S flagship line. Samsung and AMD announced a partnership to develop a mobile GPU back in .... This ensures that all AMD's Radeon Pro Duo is a beast of a dual GPU graphics card ... The Radeon Pro 5500M is a professional mobile graphics chip by AMD, ... Both NVidia's GeForce & AMD's Radeon have fantastic Graphics Cards ... While both companies are interested in the mobile and console markets, Nvidia has ... -
Case 6:19-Cv-00474-ADA Document 46 Filed 05/05/20 Page 1 of 208
Case 6:19-cv-00474-ADA Document 46 Filed 05/05/20 Page 1 of 208 IN THE UNITED STATES DISTRICT COURT FOR THE WESTERN DISTRICT OF TEXAS WACO DIVISION GPU++, LLC, ) ) Plaintiff, ) ) v. ) ) Civil Action No. W-19-CV-00474-ADA QUALCOMM INCORPORATED; ) QUALCOMM TECHNOLOGIES, INC., ) JURY TRIAL DEMANDED SAMSUNG ELECTRONICS CO., LTD.; ) SAMSUNG ELECTRONICS AMERICA, INC.; ) U.S. Dist. Ct. Judge: Hon. Alan. D. Albright SAMSUNG SEMICONDUCTOR, INC.; ) SAMSUNG AUSTIN SEMICONDUCTOR, ) LLC, ) ) Defendants. ) FIRST AMENDED COMPLAINT Plaintiff GPU++, LLC (“Plaintiff”), by its attorneys, demands a trial by jury on all issues so triable and for its complaint against Qualcomm Incorporated and Qualcomm Technologies, Inc. (collectively, “Qualcomm”) and Samsung Electronics Co., Ltd., Samsung Electronics America, Inc., Samsung Semiconductor, Inc., and Samsung Austin Semiconductor, LLC (collectively, “Samsung”) (Qualcomm and Samsung collectively, “Defendants”), and alleges as follows: NATURE OF THE ACTION 1. This is a civil action for patent infringement under the patent laws of the United States, Title 35, United States Code, Section 271, et seq., involving United States Patent No. 8,988,441 (Exhibit A, “’441 patent”) and seeking damages and injunctive relief as provided in 35 U.S.C. §§ 281 and 283-285. THE PARTIES 2. Plaintiff is a California limited liability company with a principal place of business Case 6:19-cv-00474-ADA Document 46 Filed 05/05/20 Page 2 of 208 at 650-B Fremont Avenue #137, Los Altos, CA 94024. Plaintiff is the owner by assignment of the ʼ441 patent. 3. On information and belief, Qualcomm Incorporated is a corporation organized and existing under the laws of the State of Delaware, having a principal place of business at 5775 Morehouse Dr., San Diego, California, 92121. -
Arxiv:1910.06663V1 [Cs.PF] 15 Oct 2019
AI Benchmark: All About Deep Learning on Smartphones in 2019 Andrey Ignatov Radu Timofte Andrei Kulik ETH Zurich ETH Zurich Google Research [email protected] [email protected] [email protected] Seungsoo Yang Ke Wang Felix Baum Max Wu Samsung, Inc. Huawei, Inc. Qualcomm, Inc. MediaTek, Inc. [email protected] [email protected] [email protected] [email protected] Lirong Xu Luc Van Gool∗ Unisoc, Inc. ETH Zurich [email protected] [email protected] Abstract compact models as they were running at best on devices with a single-core 600 MHz Arm CPU and 8-128 MB of The performance of mobile AI accelerators has been evolv- RAM. The situation changed after 2010, when mobile de- ing rapidly in the past two years, nearly doubling with each vices started to get multi-core processors, as well as power- new generation of SoCs. The current 4th generation of mo- ful GPUs, DSPs and NPUs, well suitable for machine and bile NPUs is already approaching the results of CUDA- deep learning tasks. At the same time, there was a fast de- compatible Nvidia graphics cards presented not long ago, velopment of the deep learning field, with numerous novel which together with the increased capabilities of mobile approaches and models that were achieving a fundamentally deep learning frameworks makes it possible to run com- new level of performance for many practical tasks, such as plex and deep AI models on mobile devices. In this pa- image classification, photo and speech processing, neural per, we evaluate the performance and compare the results of language understanding, etc. -
Michael Doggett Department of Computer Science Lund University Overview
Graphics Architectures and OpenCL Michael Doggett Department of Computer Science Lund university Overview • Parallelism • Radeon 5870 • Tiled Graphics Architectures • Important when Memory and Bandwidth limited • Different to Tiled Rasterization! • Tessellation • OpenCL • Programming the GPU without Graphics © mmxii mcd “Only 10% of our pixels require lots of samples for soft shadows, but determining which 10% is slower than always doing the samples. ” by ID_AA_Carmack, Twitter, 111017 Parallelism • GPUs do a lot of work in parallel • Pipelining, SIMD and MIMD • What work are they doing? © mmxii mcd What’s running on 16 unifed shaders? 128 fragments in parallel 16 cores = 128 ALUs MIMD 16 simultaneous instruction streams 5 Slide courtesy Kayvon Fatahalian vertices/fragments primitives 128 [ OpenCL work items ] in parallel CUDA threads vertices primitives fragments 6 Slide courtesy Kayvon Fatahalian Unified Shader Architecture • Let’s take the ATI Radeon 5870 • From 2009 • What are the components of the modern graphics hardware pipeline? © mmxii mcd Unified Shader Architecture Grouper Rasterizer Unified shader Texture Z & Alpha FrameBuffer © mmxii mcd Unified Shader Architecture Grouper Rasterizer Unified Shader Texture Z & Alpha FrameBuffer ATI Radeon 5870 © mmxii mcd Shader Inputs Vertex Grouper Tessellator Geometry Grouper Rasterizer Unified Shader Thread Scheduler 64 KB GDS SIMD 32 KB LDS Shader Processor 5 32bit FP MulAdd Texture Sampler Texture 16 Shader Processors 256 KB GPRs 8 KB L1 Tex Cache 20 SIMD Engines Shader Export Z & Alpha 4 -
I.MX Graphics Users Guide Android
NXP Semiconductors Document Number: IMXGRAPHICUG Rev. 0, 02/2018 i.MX Graphics User’s Guide Contents Chapter 1 Introduction ............................................................................................................................................. 6 Chapter 2 i.MX G2D API ............................................................................................................................................ 6 2.1 Overview ...................................................................................................................................................... 6 2.2 Enumerations and structures ....................................................................................................................... 6 2.3 G2D function descriptions .......................................................................................................................... 10 2.4 Support of new operating system in G2D .................................................................................................. 16 2.5 Sample code for G2D API usage ................................................................................................................. 16 2.6 Feature list on multiple platforms.............................................................................................................. 19 Chapter 3 i.MX EGL and OGL Extension Support .................................................................................................... 20 3.1 Introduction ..............................................................................................................................................