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Real-Time Finite Element Method (FEM) and Tressfx
REAL-TIME FEM AND TRESSFX 4 ERIC LARSEN KARL HILLESLAND 1 FEBRUARY 2016 | CONFIDENTIAL FINITE ELEMENT METHOD (FEM) SIMULATION Simulates soft to nearly-rigid objects, with fracture Models object as mesh of tetrahedral elements Each element has material parameters: ‒ Young’s Modulus: How stiff the material is ‒ Poisson’s ratio: Effect of deformation on volume ‒ Yield strength: Deformation limit before permanent shape change ‒ Fracture strength: Stress limit before the material breaks 2 FEBRUARY 2016 | CONFIDENTIAL MOTIVATIONS FOR THIS METHOD Parameters give a lot of design control Can model many real-world materials ‒Rubber, metal, glass, wood, animal tissue Commonly used now for film effects ‒High-quality destruction Successful real-time use in Star Wars: The Force Unleashed 1 & 2 ‒DMM middleware [Parker and O’Brien] 3 FEBRUARY 2016 | CONFIDENTIAL OUR PROJECT New implementation of real-time FEM for games Planned CPU library release ‒Heavy use of multithreading ‒Open-source with GPUOpen license Some highlights ‒Practical method for continuous collision detection (CCD) ‒Mix of CCD and intersection contact constraints ‒Efficient integrals for intersection constraint 4 FEBRUARY 2016 | CONFIDENTIAL STATUS Proof-of-concept prototype First pass at optimization Offering an early look for feedback Several generic components 5 FEBRUARY 2016 | CONFIDENTIAL CCD Find time of impact between moving objects ‒Impulses can prevent intersections [Otaduy et al.] ‒Catches collisions with fast-moving objects Our approach ‒Conservative-advancement based ‒Geometric -
Opengl ES, XNA, Directx for WP8) Plan
Mobilne akceleratory grafiki Kamil Trzciński, 2013 O mnie Kamil Trzciński http://ayufan.eu / [email protected] ● Od 14 lat zajmuję się programowaniem (C/C++, Java, C#, Python, PHP, itd.) ● Od 10 lat zajmuję się programowaniem grafiki (OpenGL, DirectX 9/10/11, Ray-Tracing) ● Od 6 lat zajmuję się branżą mobilną (SymbianOS, Android, iOS) ● Od 2 lat zajmuję się mobilną grafiką (OpenGL ES, XNA, DirectX for WP8) Plan ● Bardzo krótko o historii ● Mobilne układy graficzne ● API ● Programowalne jednostki cieniowania ● Optymalizacja ● Silniki graficzne oraz silniki gier Wstęp Grafika komputerowa to dziedzina informatyki zajmująca się wykorzystaniem technik komputerowych do celów wizualizacji artystycznej oraz wizualizacji rzeczywistości. Bardzo często grafika komputerowa jest kojarzona z urządzeniem wspomagającym jej generowanie - kartą graficzną, odpowiedzialna za renderowanie grafiki oraz jej konwersję na sygnał zrozumiały dla wyświetlacza 1. Historia Historia Historia kart graficznych sięga wczesnych lat 80-tych ubiegłego wieku. Pierwsze karty graficzne potrafiły jedynie wyświetlać znaki alfabetu łacińskiego ze zdefiniowanego w pamięci generatora znaków, tzw. trybu tekstowego. W późniejszym okresie pojawiły się układy, wykonujące tzw. operacje BitBLT, pozwalające na nałożenie na siebie 2 różnych bitmap w postaci rastrowej. Historia Historia #2 ● Wraz z nadejściem systemu operacyjnego Microsoft Windows 3.0 wzrosło zapotrzebowanie na przetwarzanie grafiki rastrowej dużej rozdzielczości. ● Powstaje interfejs GDI odpowiedzialny za programowanie operacji związanych z grafiką. ● Krótko po tym powstały pierwsze akceleratory 2D wyprodukowane przez firmę S3. Wydarzenie to zapoczątkowało erę graficznych akceleratorów grafiki. Historia #3 ● 1996 – wprowadzenie chipsetu Voodoo Graphics przez firmę 3dfx, dodatkowej karty rozszerzeń pełniącej funkcję akceleratora grafiki 3D. ● Powstają biblioteki umożliwiające tworzenie trójwymiarowych wizualizacji: Direct3D oraz OpenGL. Historia #3 Historia #4 ● 1999/2000 – DirectX 7.0 dodaje obsługę: T&L (ang. -
The Amd Linux Graphics Stack – 2018 Edition Nicolai Hähnle Fosdem 2018
THE AMD LINUX GRAPHICS STACK – 2018 EDITION NICOLAI HÄHNLE FOSDEM 2018 1FEBRUARY 2018 | CONFIDENTIAL GRAPHICS STACK: KERNEL / USER-SPACE / X SERVER Mesa OpenGL & Multimedia Vulkan Vulkan radv AMDVLK OpenGL X Server radeonsi Pro/ r600 Workstation radeon amdgpu LLVM SCPC libdrm radeon amdgpu FEBRUARY 2018 | AMD LINUX GRAPHICS STACK 2FEBRUARY 2018 | CONFIDENTIAL GRAPHICS STACK: OPEN-SOURCE / CLOSED-SOURCE Mesa OpenGL & Multimedia Vulkan Vulkan radv AMDVLK OpenGL X Server radeonsi Pro/ r600 Workstation radeon amdgpu LLVM SCPC libdrm radeon amdgpu FEBRUARY 2018 | AMD LINUX GRAPHICS STACK 3FEBRUARY 2018 | CONFIDENTIAL GRAPHICS STACK: SUPPORT FOR GCN / PRE-GCN HARDWARE ROUGHLY: GCN = NEW GPUS OF THE LAST 5 YEARS Mesa OpenGL & Multimedia Vulkan Vulkan radv AMDVLK OpenGL X Server radeonsi Pro/ r600 Workstation radeon amdgpu LLVM(*) SCPC libdrm radeon amdgpu (*) LLVM has pre-GCN support only for compute FEBRUARY 2018 | AMD LINUX GRAPHICS STACK 4FEBRUARY 2018 | CONFIDENTIAL GRAPHICS STACK: PHASING OUT “LEGACY” COMPONENTS Mesa OpenGL & Multimedia Vulkan Vulkan radv AMDVLK OpenGL X Server radeonsi Pro/ r600 Workstation radeon amdgpu LLVM SCPC libdrm radeon amdgpu FEBRUARY 2018 | AMD LINUX GRAPHICS STACK 5FEBRUARY 2018 | CONFIDENTIAL MAJOR MILESTONES OF 2017 . Upstreaming the DC display driver . Open-sourcing the AMDVLK Vulkan driver . Unified driver delivery . OpenGL 4.5 conformance in the open-source Mesa driver . Zero-day open-source support for new hardware FEBRUARY 2018 | AMD LINUX GRAPHICS STACK 6FEBRUARY 2018 | CONFIDENTIAL KERNEL: AMDGPU AND RADEON HARDWARE SUPPORT Pre-GCN radeon GCN 1st gen (Southern Islands, SI, gfx6) GCN 2nd gen (Sea Islands, CI(K), gfx7) GCN 3rd gen (Volcanic Islands, VI, gfx8) amdgpu GCN 4th gen (Polaris, RX 4xx, RX 5xx) GCN 5th gen (RX Vega, Ryzen Mobile, gfx9) FEBRUARY 2018 | AMD LINUX GRAPHICS STACK 7FEBRUARY 2018 | CONFIDENTIAL KERNEL: AMDGPU VS. -
Radeon GPU Profiler Documentation
Radeon GPU Profiler Documentation Release 1.11.0 AMD Developer Tools Jul 21, 2021 Contents 1 Graphics APIs, RDNA and GCN hardware, and operating systems3 2 Compute APIs, RDNA and GCN hardware, and operating systems5 3 Radeon GPU Profiler - Quick Start7 3.1 How to generate a profile.........................................7 3.2 Starting the Radeon GPU Profiler....................................7 3.3 How to load a profile...........................................7 3.4 The Radeon GPU Profiler user interface................................. 10 4 Settings 13 4.1 General.................................................. 13 4.2 Themes and colors............................................ 13 4.3 Keyboard shortcuts............................................ 14 4.4 UI Navigation.............................................. 16 5 Overview Windows 17 5.1 Frame summary (DX12 and Vulkan).................................. 17 5.2 Profile summary (OpenCL)....................................... 20 5.3 Barriers.................................................. 22 5.4 Context rolls............................................... 25 5.5 Most expensive events.......................................... 28 5.6 Render/depth targets........................................... 28 5.7 Pipelines................................................. 30 5.8 Device configuration........................................... 33 6 Events Windows 35 6.1 Wavefront occupancy.......................................... 35 6.2 Event timing............................................... 48 6.3 -
Augmented Hair in Deus Ex Universe Projects: Tressfx 3.0 Jason Stewart (Amd) Uriel Doyon (Eidos-Montréal) Thursday, March 5, 2015 High-Level Agenda
AUGMENTED HAIR IN DEUS EX UNIVERSE PROJECTS: TRESSFX 3.0 JASON STEWART (AMD) URIEL DOYON (EIDOS-MONTRÉAL) THURSDAY, MARCH 5, 2015 HIGH-LEVEL AGENDA Brief TressFX overview TressFX in the Dawn Engine ‒ New engine from Eidos-Montréal ‒ Cornerstone for all Deus Ex Universe projects TressFX 3.0 library ‒ Update to AMD’s TressFX example implementation ‒ Maya plugin ‒ Viewer and runtime library (with full source) ‒ Fur support ‒ Skinning ‒ Latest optimizations 2 | TRESSFX 3.0 | THURSDAY, MARCH 5 | GDC 2015 A BRIEF HISTORY TressFX began as a collaboration between AMD and Crystal Dynamics First used in Tomb Raider ‒ PC and consoles ‒ Set new quality bar for hair in games Optimized for AMD GCN architecture ‒ Radeon HD 7000 or later ‒ PS4, Xbox One AMD is now also collaborating with Eidos-Montréal ‒ Started with Tomb Raider code ‒ Improvements and additions integrated into Dawn Engine ‒ Will be used in future Deus Ex Universe projects 3 | TRESSFX 3.0 | THURSDAY, MARCH 5 | GDC 2015 TRESSFX OVERVIEW Two parts to TressFX ‒ Physics simulation on the GPU using compute shaders ‒ High-quality rendering Simulates and renders individual hair strands initial goal position current position final position SIMULATION RENDERING 4 | TRESSFX 3.0 | THURSDAY, MARCH 5 | GDC 2015 TRESSFX SIMULATION Simulation initial goal position parameters final position current position SIMULATION COMPUTE SHADERS ‒ Edge length constraint ‒ Local shape constraint CSCS CS ‒ Global shape constraint ‒ Model Transform ‒ Collision Shape Constraints Post-simulation ‒ External Forces (wind, gravity, etc.) (SRV) geometry (UAV) Input Geometry Post-simulation line (SRV) segments (world space) Pre-simulation line segments (model space) 5 | TRESSFX 3.0 | THURSDAY, MARCH 5 | GDC 2015 TRESSFX RENDERING Good Lighting + Anti-Aliasing + Volume Shadows + Transparency 6 | TRESSFX 3.0 | THURSDAY, MARCH 5 | GDC 2015 PureHair Overview • Data Model • Hair Strands • Simulation PureHair. -
Real-Time Hair Rendering
Real-Time Hair Rendering Master Thesis Computer Science and Media M.Sc. Stuttgart Media University Markus Rapp Matrikel-Nr.: 25823 Erstprüfer: Stefan Radicke Zweitprüfer: Simon Spielmann Stuttgart, 7. November 2014 Real-Time Hair Rendering Abstract A b s t r a c t An approach is represented to render hair in real-time by using a small number of guide strands to generate interpolated hairs on the graphics processing unit (GPU). Hair interpolation methods are based on a single guide strand or on multiple guide strands. Each hair strand is composed by segments, which can be further subdivided to render smooth hair curves. The appearance of the guide hairs as well as the size of the hair segments in screen space are used to calculate the amount of detail, which is needed to display smooth hair strands. The developed hair rendering system can handle guide strands with different segment counts. Included features are curly hair, thinning and random deviations. The open graphics library (OpenGL) tessellation rendering pipeline is utilized for hair generation. The hair rendering algorithm was integrated into the Frapper’s character rendering pipeline. Inside Frapper, configuration of the hair style can be adjusted. Development was done in cooperation with the Animation Institute of Filmakademie Baden- Württemberg within the research project “Stylized Animations for Research on Autism” (SARA). Keywords: thesis, hair, view-dependent level of detail, tessellation, OpenGL, Ogre, Frapper i Real-Time Hair Rendering Declaration of Originality Declaration of O r i g i n a l i t y I hereby certify that I am the sole author of this thesis and that no part of this thesis has been published or submitted for publication. -
Virtualdub Help
VirtualDub help Welcome to the new helpfile for VirtualDub 1.5+. The old help file used to have some general tips on how to create video, but I've come to the conclusion that such a help file is too much effort to maintain and that my efforts in this area are better spent explaining what the options do rather than how to use them. So, currently, this help file currently consists of comprehensive explanations of what various settings dialogs in VirtualDub do. VirtualDub help - Processing: Main UI Display panes Two rectangular panes occupy most of VirtualDub's interface; the left one is the input pane and the right one is the output pane. As the current position is moved through the video, the panes will update with the original and filtered result of that frame. This allows convenient before-and-after comparisons of the video. The positioning and size of the display panes can be modified in a number of ways; see Display panes for more information. Position slider Drag the slider below the panes to change the current position within the video. If enabled, the display panes will update to show the selected frame. Holding Shift while dragging forces the current position to be placed only on key frames. Using the right mouse button to drag the slider instead of the left causes the drag to occur at a much slower rate for more precise positioning. Each position on the position slider corresponds to the start of each frame in the video timeline. As a result, there is one additional position at the end corresponding to the end of the video. -
AMD's Graphics Core Next (GCN) Architecture
AMD’s Graphics Core Next (GCN) Architecture Tony Chen Jason Greaves Overview ● Terascale ○ Limitation ● GCN architecture ○ Revisions ■ Features/Updates ● Mantle Terascale ● ~2006 - 2011 ● VLIW SIMD (Very Long Instruction Word Single Instruction Multiple Data) ● Meant to compete with Nvidia’s Tesla line ● Ranged from the Radeon HD 2000 - 6000 series graphics cards ● Found in some of the early APUs ● VLIW4 ● One SIMD engine o 16 shader processor . 4 ALUs each o 64 ALUs per SIMD engine The problem ● Terascale’s VLIW architecture o Very good for graphics instructions o compiler optimized for dot product math . cannot change the wavefront (instruction set) queue once it has been scheduled o High instruction level parallelism o Specialized hardware design . Double edge sword . Not good for general computing . Cannot continue until a dependency has been resolved http://www.tomshardware.com/reviews/radeon- hd-7970-benchmark-tahiti-gcn,3104-2.html GCN architecture ● Released early 2012 (announced late 2011) ● Select Radeon HD 7000s, 8000s, and Rx 200 series ● 28nm technology TSMC ● RISC SIMD (Reduced instruction set computing Single Instruction Multiple Data) ● Designed for general computing GCN Compute Unit ● Compute Unit (CU) o 4 vector units . 16 ALUs each . Scheduler ● Independent ● Can avoid dependencies o 64 ALUs per CU GCN Architecture ● HyperZ ● GCN 1.0 o PowerTune o ZeroCore power ● GCN 1.1 ● GCN 1.2 HyperZ ● November 2000 ● developed by ATI (Array Technologies Inc) ● Processing technique for Z-buffering o Algorithm to determine which depth to use for a single pixel space o About ~50% of bandwidth used for Z-Buffer read/write ● Boost memory bandwidth / Improves efficiency o Compresses data (lossless format) to minimize bandwidth for reads and writes o Tags blocks of data instead of writing individual bits o Compares pixels before rendering to save bandwidth ● Updates over time(ex:HyperZ II, HyperZ HD) GCN 1.0 ● Supports 64 bit addressing ● Backwards compatible with 16 and 32 bit ● Unified virtual memory between CPU and GPU o Zero copy . -
Virtualdub Help Seite 1 Von 1
VirtualDub help Seite 1 von 1 VirtualDub help Welcome to the new helpfile for VirtualDub 1.5+. The old help file used to have some general tips on how to create video, but I've come to the conclusion that such a help file is too much effort to maintain and that my efforts in this area are better spent explaining what the options do rather than how to use them. So, currently, this help file currently consists of comprehensive explanations of what various settings dialogs in VirtualDub do. file://C:\Dokumente und Einstellungen\Helmut\Lokale Einstellungen\Temp\~hhCCD5... 03.04.2008 Processing: Main UI Seite 1 von 29 VirtualDub help - Processing: Main UI Display panes Two rectangular panes occupy most of VirtualDub's interface; the left one is the input pane and the right one is the output pane. As the current position is moved through the video, the panes will update with the original and filtered result of that frame. This allows convenient before-and-after comparisons of the video. The positioning and size of the display panes can be modified in a number of ways; see Display panes for more information. Position slider Drag the slider below the panes to change the current position within the video. If enabled, the display panes will update to show the selected frame. Holding Shift while dragging forces the current position to be placed only on key frames. Using the right mouse button to drag the slider instead of the left causes the drag to occur at a much slower rate for more precise positioning. -
AMD Graphics Core Next (GCN) Architecture
White Paper | AMD GRAPHICS CORES NEXT (GCN) ARCHITECTURE Table of Contents INTRODUCTION 2 COMPUTE UNIT OVERVIEW 3 CU FRONT-END 5 SCALAR EXECUTION AND CONTROL FLOW 5 VECTOR EXECUTION 6 VECTOR REGISTERS 6 VECTOR ALUS 7 LOCAL DATA SHARE AND ATOMICS 7 EXPORT 8 VECTOR MEMORY 8 L2 CACHE, COHERENCY AND MEMORY 10 PROGRAMMING MODEL 11 SYSTEM ARCHITECTURE 11 GRAPHICS ARCHITECTURE 12 PROGRAMMABLE VIDEO PROCESSING 16 RELIABLE COMPUTING 16 CONCLUSION 17 June, 2012 INTRODUCTION Over the last 15 years, graphics processors have continually evolved and are on the cusp of becoming an integral part of the computing landscape. The first designs employed special purpose hardware with little flexibility. Later designs introduced limited programmability through shader programs, and eventually became highly programmable throughput computing devices that still maintained many graphics-specific capabilities. Figure 1: GPU Evolution The performance and efficiency potential of GPUs is incredible. Games provide visual quality comparable to leading films, and early adopters in the scientific community have seen an order of magnitude improvement in performance, with high-end GPUs capable of exceeding 4 TFLOPS (Floating point Operations per Second). The power efficiency is remarkable as well; for example, the AMD Radeon™ HD 7770M GPU achieves over 1 TFLOPS with a maximum power draw of 45W. Key industry standards, such as OpenCL™, DirectCompute and C++ AMP recently have made GPUs accessible to programmers. The challenge going forward is creating seamless heterogeneous computing solutions for mainstream applications. This entails enhancing performance and power efficiency, but also programmability and flexibility. Mainstream applications demand industry standards that are adapted to the modern ecosystem with both CPUs and GPUs and a wide range of form factors from tablets to supercomputers. -
GPU Developments 2016
GPU Developments 2016 GPU developments during 2016 © Copyright Jon Peddie Research 2016. 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. The contents of this report represent the interpretation and analysis of statistics and information that is either generally available to the public or released by responsible agencies or individuals. The information contained in this report is believed to be reliable but is not guaranteed as to its accuracy or completeness. Jon Peddie Research reserves all rights herein. Reproduction or disclosure in whole or in part to parties other than the Jon Peddie Research client who is the original subscriber to this report is permitted only with the written and express consent of Jon Peddie Research. This report shall be treated at all times as a confidential and proprietary document for internal use only. Jon Peddie Research reserves the right to cancel your subscription or contract in full if its information is copied or distributed to other divisions of the subscribing company without the written approval of Jon Peddie Research. This report contains a “review” of various products. It is not an endorsement or attempt to sell any products. Under the rules of the “Fair Use Doctrine,” JPR assumes no responsibility for the correct or incorrect usage of any trademarks or service marks. Authentic copies of this Report feature the Logo above and this Red color bar Page ii of 22 Copyright 2016 Jon Peddie Research GPU developments during 2016 Table of Contents Executive Summary ................................................................................................ -
AMD” Or “Defendant”) Infringes Each of the Patents-In-Suit In
Case 1:18-cv-01715-CFC Document 16 Filed 01/28/19 Page 1 of 211 PageID #: 327 IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF DELAWARE DYNAMIC DATA TECHNOLOGIES, LLC, Plaintiff, v. Civil Action No. 18-cv-01715-CFC ADVANCED MICRO DEVICES, INC., JURY TRIAL DEMANDED Defendant. FIRST AMENDED COMPLAINT FOR PATENT INFRINGEMENT Dynamic Data Technologies, LLC (“Dynamic Data”) brings this action and makes the following allegations of patent infringement relating to U.S. Patent Nos.: 8,189,105 (the “’105 Patent”); 8,135,073 (the “‘073 Patent”); 7,532,220 (the “‘220 Patent”); 6,714,257 (the “‘257 Patent”); 8,073,054 (the “‘054 Patent”); 6,774,918 (the “‘918 Patent”); 8,184,689 (the “‘689 Patent”); 6,996,177 (the “‘177 Patent”); 7,010,039 (the “‘039 Patent”); 8,311,112 (the “‘112 Patent”); 6,646,688 (the “‘688 Patent”); 7,894,529 (the “‘529 Patent”); 7,542,041 (the “‘041 Patent”); 7,571,450 (the “‘450 Patent”); 7,750,979 (the “‘979 Patent”); 7,058,227 (the “’227 Patent”); and 6,421,090 (the “‘090 Patent”) (collectively, the “patents-in-suit”). Defendant Advanced Micro Devices, Inc. (“AMD” or “Defendant”) infringes each of the patents-in-suit in violation of the patent laws of the United States of America, 35 U.S.C. § 1 et seq. CO-PENDING ENFORCEMENT PROCEEDINGS IN THE PEOPLE’S REPUBLIC OF CHINA AND PATENT PORTFOLIO EXPANSION 1. Dynamic Data’s portfolio of over 1,200 patent assets encompasses core technologies in the field of image and video processing. The patent portfolio held by Dynamic Data is international in scope and includes several hundred European and Chinese patent grants.