DOCSLIB.ORG

Ray Tracing, Part 1 of 2: Intersections, Ray Trees & Recursion

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Ray Tracing, Part 1 of 2: Intersections, Ray Trees & Recursion 2 Lecture 31of 41 Lecture Outline Ray Tracing, Part 1 of 2: Reading for Last Class: §5.3, Eberly 2e; CGA Handout Intersections, Ray Trees & Recursion Reading for Today: Chapter 14, Eberly 2e Reading for Next Class: Ray Tracing Handout Last Time: Animation Part 3 of 3 – Inverse Kinematics William H. Hsu FK vs. IK Department of Computing and Information Sciences, KSU IK Autonomous agents vs. hand-animated movement KSOL course pages: http://bit.ly/hGvXlH / http://bit.ly/eVizrE Public mirror web site: http://www.kddresearch.org/Courses/CIS636 Analytical vs. iterative solutions Instructor home page: http://www.cis.ksu.edu/~bhsu Rag doll physics, rigid-body dynamics, physically-based models End of Material on: Particle Systems, Collisions, CGA, PBM Readings: Today: Ray Tracing, Part 1 of 2 Last class: §5.3, Eberly 2e – see http://bit.ly/ieUq45; CGA Handout Vectors: Light/shadow (L), Reflected (R), Transmitted/refracted (T) Today: Chapter 14, Eberly 2e Next class: Ray Tracing Handout Basic recursive ray tracing: ray trees Reference – Wikipedia, Ray Tracing: http://bit.ly/dV7lNm Next Class: Ray Tracing Lab Reference – ACM Ray Tracing News: http://bit.ly/fqyZNQ CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 3 4 Acknowledgements: Where We Are Inverse Kinematics, Ray Tracing David C. Brogan Visiting Assistant Professor, Computer Science Department, University of Virginia http://www.cs.virginia.edu/~dbrogan/ Susquehanna International Group (SIG) http://www.sig.com Renata Melamud Ph.D. Candidate Mechanical Engineering Department Stanford University http://micromachine.stanford.edu/~rmelamud/ Dave Shreiner & Brad Grantham Adjunct Professor & Adjunct Lecturer, Santa Clara University ARM Holdings, plc http://www.plunk.org/~shreiner/ http://www.plunk.org/~grantham/ CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 5 Review [1]: 6 Review [2]: Kinematics & Degrees of Freedom Joint Types Adapted from slides 2000 – 2005 D. Brogan, University of Virginia Adapted from slides 2002 R. Melamud, Stanford University CS 551, Advanced CG & Animation – http://bit.ly/hUXrqd Mirrored at CMU 16-311 Introduction to Robotics, http://generalrobotics.org CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 7 Forward Kinematics: 8 Review [3]: Joint Angles to Bone Coordinates Forward Kinematics ? 3 2 End Effector 1 Base θx )f( f Φe Choi Rotenberg Adapted from slides 2004 – 2005 S. Rotenberg, UCSD Adapted from slides 2002 K. J. Choi, Seoul National University CSE169: Computer Animation, Winter 2005 – http://bit.ly/f0ViAN Graphics and Media Lab ( http://graphics.snu.ac.kr ) – mirrored at: http://bit.ly/hnzSAN CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 9 Review [4]: 10 Inverse Kinematics: Inverse Kinematics Issues For more on characters & IK, see: Advanced Topics in CG Lecture 05 ? 3 2 ? End Effector 1 Base 1 xθ )(f f 1eΦ Choi Rotenberg Adapted from slides 2002 K. J. Choi, Seoul National University Adapted from slides 2004 – 2005 S. Rotenberg, UCSD Graphics and Media Lab ( http://graphics.snu.ac.kr) – mirrored at: http://bit.ly/hnzSAN CSE169: Computer Animation, Winter 2005 – http://bit.ly/f0ViAN CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 11 Review [5]: 12 Review [6]: Inverse Kinematics Demos Ragdoll Physics Type of Procedural Animation Automatically generates CGA directives (rotations) Based on simulation Rigid-body dynamics Articulated Figure Gravity © 2008 M. Kinzelman © 2007 A. Brown No autonomous movement http://youtu.be/l52yZ491kPo http://youtu.be/6JdLOLazJJ0 Falling Bodies © 1997 – 2001 Animats Used for inert body http://www.animats.com Usually: character death (car impact, falling body, etc.) Less often: unconscious, paralyzed character Collisions with Multiple Bodies Inter-character Character-object © 2008 T. Komura, H. S. Lim, & R. W. H. Lau © 2011 K. Iyer http://youtu.be/FJTBMnP6oCM http://youtu.be/YvRBWIRAPsE CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 13 Review [7]: 14 Review [8}: Ragdoll Physics Demos Physically-Based Modeling (PBM) Particle Dynamics Emitters 0-D (points), 1-D (lines), 2-D (planes, discs, cross-sections) e.g., fireworks (0-D); fountains (0/1/2-D); smokestacks, jets (2-D) Simulation: birth-death process, functions of particle age/trajectory Rigid-Body Dynamics © 2006 P. Pelt © 2007 N. Picouet http://youtu.be/6JdLOLazJJ0 Constrained systems of connected parts http://youtu.be/ohNqCb--aSs See also: http://youtu.be/5_QIsI0fyaU Examples: falling rocks, colliding vehicles, rag dolls Articulated Figures: Primarily IK Rocks fall More References Everyone dies ACM, Intro to Physically-Based Modeling : http://bit.ly/hhQvXd Wikipedia, Physics Engine: http://bit.ly/h4PIRt Wikipedia, N-Body Problem: http://bit.ly/1ayWwe PBM System: nVidia (Ageia) PhysX: http://bit.ly/cp7bnA © 2009 M. E. Cerquoni © 2010 M. Heinzen (Arkaein) http://youtu.be/uW_DK2qvKv8 http://bit.ly/gUj9Su / http://youtu.be/FJTBMnP6oCM CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 15 Ray Tracing [1]: 16 Ray Tracing [2]: Overview Why Use It? What is it? Simulate rays of light Why use it? Produces natural lighting effects Basics Advanced topics Reflection Depth of Field References Refraction Motion Blur © 2006 – 2007 H. Kuijpers, Soft Shadows Caustics Capgemini Netherlands http://bit.ly/erkKrC Hard to simulate effects with rasterization techniques (OpenGL) Rasterizers require many passes Ray-tracing easier to implement Adapted from slides 2001 D. Shreiner & B. Grantham, SCU Adapted from slides 2001 D. Shreiner & B. Grantham, SCU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 17 Ray Tracing [3]: 18 Ray Tracing [4]: Who Uses It? Brief History Entertainment (Movies, Commercials) Decartes, 1637 A.D. - analysis of rainbow Games pre-production Arthur Appel, 1968 - used for lighting 3D models Simulation Turner Whitted, 1980 - “An Improved Illumination Model for Shaded Display” really kicked everyone off. 1980-now - Lots of research Adapted from slides 2001 D. Shreiner & B. Grantham, SCU Adapted from slides 2001 D. Shreiner & B. Grantham, SCU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 19 Ray Tracing [5]: 20 Ray Tracing [6]: Basic Operations Basic Idea Simulate light rays from light source to eye Generating Rays Intersecting Rays with Scene Lighting Eye Light Shadowing Reflections ay Inc ed r iden lect t ray Ref Surface Adapted from slides 2001 D. Shreiner & B. Grantham, SCU Adapted from slides 2001 D. Shreiner & B. Grantham, SCU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas State University 21 22 “Forward” Ray Tracing “Backward” Ray Tracing Trace rays from light Trace rays from eye instead Lots of work for little return Do work where it matters Light Light Image Image Light Rays Plane Plane Eye Eye Object Object This is what most people mean by “ray tracing”. Adapted from slides 2001 D. Shreiner & B. Grantham, SCU Adapted from slides 2001 D. Shreiner & B. Grantham, SCU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU COEN 290: Computer Graphics I, Winter 2001 – http://bit.ly/hz1kfU CIS 536/636 Computing & Information Sciences CIS 536/636 Computing & Information Sciences Lecture 31 of 41 Lecture 31 of 41 Introduction to Computer Graphics Kansas State University Introduction to Computer Graphics Kansas
Load more

Recommended publications
  • Physx As a Middleware for Dynamic Simulations in the Container Loading Problem
    Proceedings of the 2018 Winter Simulation Conference M. Rabe, A.A. Juan, N. Mustafee, A. Skoogh, S. Jain, and B. Johansson, eds. PHYSX AS A MIDDLEWARE FOR DYNAMIC SIMULATIONS IN THE CONTAINER LOADING PROBLEM Juan C. Martínez-Franco David Álvarez-Martínez Department of Mechanical Engineering Department of Industrial Engineering Universidad de Los Andes Universidad de Los Andes Carrera 1 Este No. 19A – 40 Carrera 1 Este No. 19A – 40 Bogotá, 11711, COLOMBIA Bogotá, 11711, COLOMBIA ABSTRACT The Container Loading Problem (CLP) is an optimization challenge where the constraint of dynamic stability plays a significant role. The evaluation of dynamic stability requires the use of dynamic simulations that are carried out either with dedicated simulation software that produces very small errors at the expense of simulation speed, or real-time physics engines that complete simulations in a very short time at the cost of repeatability. One such engine, PhysX, is evaluated to determine the feasibility of its integration with the open source application PackageCargo. A simulation tool based on PhysX is proposed and compared with the dynamic simulation environment of Autodesk Inventor to verify its reliability. The simulation tool presents a dynamically accurate representation of the physical phenomena experienced by cargo during transportation, making it a viable option for the evaluation of dynamic stability in solutions to the CLP. 1 INTRODUCTION The Container Loading Problem (CLP) consists of the geometric arrangement of small rectangular items (cargo) into a larger rectangular space (container), but it is not a simple geometry problem. The arrangements of cargo must maximize volume utilization while complying with certain constraints such as cargo fragility, delivery order, etc.
    [Show full text]
  • Energy-Efficient VLSI Architectures for Next
    UNIVERSITY OF CALIFORNIA Los Angeles Energy-Efficient VLSI Architectures for Next- Generation Software-Defined and Cognitive Radios A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical Engineering by Fang-Li Yuan 2014 c Copyright by Fang-Li Yuan 2014 ABSTRACT OF THE DISSERTATION Energy-Efficient VLSI Architectures for Next- Generation Software-Defined and Cognitive Radios by Fang-Li Yuan Doctor of Philosophy in Electrical Engineering University of California, Los Angeles, 2014 Professor Dejan Markovic,´ Chair Dedicated radio hardware is no longer promising as it was in the past. Today, the support of diverse standards dictates more flexible solutions. Software-defined radio (SDR) provides the flexibility by replacing dedicated blocks (i.e. ASICs) with more general processors to adapt to various functions, standards and even allow mutable de- sign changes. However, such replacement generally incurs significant efficiency loss in circuits, hindering its feasibility for energy-constrained devices. The capability of dy- namic and blind spectrum analysis, as featured in the cognitive radio (CR) technology, makes chip implementation even more challenging. This work discusses several design techniques to achieve near-ASIC energy effi- ciency while providing the flexibility required by software-defined and cognitive radios. The algorithm-architecture co-design is used to determine domain-specific dataflow ii structures to achieve the right balance between energy efficiency and flexibility. The flexible instruction-set-architecture (ISA), the multi-scale interconnects, and the multi- core dynamic scheduling are also proposed to reduce the energy overhead. We demon- strate these concepts on two real-time blind classification chips for CR spectrum anal- ysis, as well as a 16-core processor for baseband SDR signal processing.
    [Show full text]
  • The Growing Importance of Ray Tracing Due to Gpus
    NVIDIA Application Acceleration Engines advancing interactive realism & development speed July 2010 NVIDIA Application Acceleration Engines A family of highly optimized software modules, enabling software developers to supercharge applications with high performance capabilities that exploit NVIDIA GPUs. Easy to acquire, license and deploy (most being free) Valuable features and superior performance can be quickly added App’s stay pace with GPU advancements (via API abstraction) NVIDIA Application Acceleration Engines PhysX physics & dynamics engine breathing life into real-time 3D; Apex enabling 3D animators CgFX programmable shading engine enhancing realism across platforms and hardware SceniX scene management engine the basis of a real-time 3D system CompleX scene scaling engine giving a broader/faster view on massive data OptiX ray tracing engine making ray tracing ultra fast to execute and develop iray physically correct, photorealistic renderer, from mental images making photorealism easy to add and produce © 2010 Application Acceleration Engines PhysX • Streamlines the adoption of latest GPU capabilities, physics & dynamics getting cutting-edge features into applications ASAP, CgFX exploiting the full power of larger and multiple GPUs programmable shading • Gaining adoption by key ISVs in major markets: SceniX scene • Oil & Gas Statoil, Open Inventor management • Design Autodesk, Dassault Systems CompleX • Styling Autodesk, Bunkspeed, RTT, ICIDO scene scaling • Digital Content Creation Autodesk OptiX ray tracing • Medical Imaging N.I.H iray photoreal rendering © 2010 Accelerating Application Development App Example: Auto Styling App Example: Seismic Interpretation 1. Establish the Scene 1. Establish the Scene = SceniX = SceniX 2. Maximize interactive 2. Maximize data visualization quality + quad buffered stereo + CgFX + OptiX + volume rendering + ambient occlusion 3.
    [Show full text]
  • NVIDIA Physx SDK EULA
    NVIDIA CORPORATION NVIDIA® PHYSX® SDK END USER LICENSE AGREEMENT Welcome to the new world of reality gaming brought to you by PhysX® acceleration from NVIDIA®. NVIDIA Corporation (“NVIDIA”) is willing to license the PHYSX SDK and the accompanying documentation to you only on the condition that you accept all the terms in this License Agreement (“Agreement”). IMPORTANT: READ THE FOLLOWING TERMS AND CONDITIONS BEFORE USING THE ACCOMPANYING NVIDIA PHYSX SDK. IF YOU DO NOT AGREE TO THE TERMS OF THIS AGREEMENT, NVIDIA IS NOT WILLING TO LICENSE THE PHYSX SDK TO YOU. IF YOU DO NOT AGREE TO THESE TERMS, YOU SHALL DESTROY THIS ENTIRE PRODUCT AND PROVIDE EMAIL VERIFICATION TO [email protected] OF DELETION OF ALL COPIES OF THE ENTIRE PRODUCT. NVIDIA MAY MODIFY THE TERMS OF THIS AGREEMENT FROM TIME TO TIME. ANY USE OF THE PHYSX SDK WILL BE SUBJECT TO SUCH UPDATED TERMS. A CURRENT VERSION OF THIS AGREEMENT IS POSTED ON NVIDIA’S DEVELOPER WEBSITE: www.developer.nvidia.com/object/physx_eula.html 1. Definitions. “Licensed Platforms” means the following: - Any PC or Apple Mac computer with a NVIDIA CUDA-enabled processor executing NVIDIA PhysX; - Any PC or Apple Mac computer running NVIDIA PhysX software executing on the primary central processing unit of the PC only; - Any PC utilizing an AGEIA PhysX processor executing NVIDIA PhysX code; - Microsoft XBOX 360; - Nintendo Wii; and/or - Sony Playstation 3 “Physics Application” means a software application designed for use and fully compatible with the PhysX SDK and/or NVIDIA Graphics processor products, including but not limited to, a video game, visual simulation, movie, or other product.
    [Show full text]
  • Shippensburg University Investment Management Program
    Shippensburg University Investment Management Program Hold NVIDIA Corp. (NASDAQ: NVDA) 11.03.2020 Current Price Fair Value 52 Week Range $501.36 $300 $180.68 - 589.07 Analyst: Valentina Alonso Key Stock Statistics Email: [email protected] Sector: Information Technology Revenue (TTM) $13.06B Stock Type: Large Growth Operating Margin (TTM) 28.56% Industry: Semiconductors and Semiconductors Equipment Market Cap: $309.697B Net Income (TTM) $3.39B EPS (TTM) $5.44 Operating Cash Flow (TTM) $5.58B Free Cash Flow (TTM) $3.67B Return on Assets (TTM) 11.67% Return on Equity (TTM) 27.94% P/E $92.59 Company overview P/B $22.32 Nvidia is the leading designer of graphics processing units that P/S $23.29 enhance the experience on computing platforms. The firm's chips are used in a variety of end markets, including high-end PCs for gaming, P/FCF 44.22 data centers, and automotive infotainment systems. In recent years, the firm has broadened its focus from traditional PC graphics Beta (5-Year) 1.54 applications such as gaming to more complex and favorable Dividend Yield 0.13% opportunities, including artificial intelligence and autonomous driving, which leverage the high-performance capabilities of the Projected 5 Year Growth 17.44% firm's graphics processing units. (per annum) Contents Executive Summary ....................................................................................................................................................3 Company Overview ....................................................................................................................................................4
    [Show full text]
  • Manycore GPU Architectures and Programming, Part 1
    Lecture 19: Manycore GPU Architectures and Programming, Part 1 Concurrent and Mul=core Programming CSE 436/536, [email protected] www.secs.oakland.edu/~yan 1 Topics (Part 2) • Parallel architectures and hardware – Parallel computer architectures – Memory hierarchy and cache coherency • Manycore GPU architectures and programming – GPUs architectures – CUDA programming – Introduc?on to offloading model in OpenMP and OpenACC • Programming on large scale systems (Chapter 6) – MPI (point to point and collec=ves) – Introduc?on to PGAS languages, UPC and Chapel • Parallel algorithms (Chapter 8,9 &10) – Dense matrix, and sorng 2 Manycore GPU Architectures and Programming: Outline • Introduc?on – GPU architectures, GPGPUs, and CUDA • GPU Execuon model • CUDA Programming model • Working with Memory in CUDA – Global memory, shared and constant memory • Streams and concurrency • CUDA instruc?on intrinsic and library • Performance, profiling, debugging, and error handling • Direc?ve-based high-level programming model – OpenACC and OpenMP 3 Computer Graphics GPU: Graphics Processing Unit 4 Graphics Processing Unit (GPU) Image: h[p://www.ntu.edu.sg/home/ehchua/programming/opengl/CG_BasicsTheory.html 5 Graphics Processing Unit (GPU) • Enriching user visual experience • Delivering energy-efficient compung • Unlocking poten?als of complex apps • Enabling Deeper scien?fic discovery 6 What is GPU Today? • It is a processor op?mized for 2D/3D graphics, video, visual compu?ng, and display. • It is highly parallel, highly multhreaded mulprocessor op?mized for visual
    [Show full text]
  • Tegra: Mobile & GPU Supercomputing Convergence | GTC 2013
    Tegra – at the Convergence of Mobile and GPU Supercomputing Neil Trevett, VP Mobile Content, NVIDIA © 2012 NVIDIA - Page 1 Welcome to the Inaugural GTC Mobile Summit! Tuesday Afternoon - Room 210C Ecosystem Broad View – including Ouya Development Tools – including Tegra 4 and Shield Wednesday Morning - Marriott Ballroom 3 Visualization – including using H.264 for still imagery Augmented device interaction – including depth camera on Tegra Wednesday Afternoon - Room 210C Vision and Computational Photography – including Chimera Web – the fastest mobile browser Mobile Panel – your chance to ask gnarly questions! Select Mobile Summit Tag in your GTC Mobile App! © 2012 NVIDIA - Page 2 Why Mobile GPU Compute? State-of-the-art Augmented Reality without GPU Compute Courtesy Metaio http://www.youtube.com/watch?v=xw3M-TNOo44&feature=related © 2012 NVIDIA - Page 3 Augmented Reality with GPU Compute Research today on CUDA equipped laptop PCs How will this GPU Compute Capability migrate from high- end PCs to mobile? High-Quality Reflections, Refractions, and Caustics in Augmented Reality and their Contribution to Visual Coherence P. Kán, H. Kaufmann, Institute of Software Technology and Interactive Systems, Vienna University of Technology, Vienna, Austria © 2012 NVIDIA - Page 4 Denver CPU Mobile SOC Performance Increases Maxwell GPU FinFET Full Kepler GPU CUDA 5.0 OpenGL 4.3 100 Parker Google Nexus 7 Logan HTC One X+ 100x perf increase in Tegra 4 four years 1st Quad A15 10 Chimera Computational Photography Core i5 Tegra 3 1st Quad A9 1st Power saver 5th core Core 2 Duo Tegra 2 st CPU/GPU AGGREGATE PERFORMANCE AGGREGATE CPU/GPU 1 Dual A9 1 2012 2013 2014 2015 2011 Device Shipping Dates © 2012 NVIDIA - Page 5 Power is the New Design Limit The Process Fairy keeps bringing more transistors.
    [Show full text]
  • NVIDIA Geforce RTX 2070 User Guide | 3 Introduction
    2070 TABLE OF CONTENTS TABLE OF CONTENTS ........................................................................................... ii 01 INTRODUCTION ............................................................................................... 3 About This Guide ................................................................................................................................ 3 Minimum System Requirements ........................................................................................................ 4 02 UNPACKING ..................................................................................................... 5 Equipment ........................................................................................................................................... 6 03 Hardware Installation ....................................................................................... 7 Safety Instructions ............................................................................................................................. 7 Before You Begin ................................................................................................................................ 8 Installing the GeForce Graphics Card ............................................................................................... 8 04 SOFTWARE INSTALLATION ........................................................................... 11 GeForce Experience Software Installation .....................................................................................
    [Show full text]
  • Reviewer's Guide
    Reviewer’s Guide NVIDIA® GeForce® GTX 280 GeForce® GTX 260 Graphics Processing Units TABLE OF CONTENTS NVIDIA GEFORCE GTX 200 GPUS.....................................................................3 Two Personalities, One GPU ........................................................................................................ 3 Beyond Gaming ............................................................................................................................. 3 GPU-Powered Video Transcoding............................................................................................... 3 GPU Powered Folding@Home..................................................................................................... 4 Industry wide support for CUDA.................................................................................................. 4 Gaming Beyond ............................................................................................................................. 5 Dynamic Realism.......................................................................................................................... 5 Introducing GeForce GTX 200 GPUs ........................................................................................... 9 Optimized PC and Heterogeneous Computing.......................................................................... 9 GeForce GTX 200 GPUs – Architectural Improvements.......................................................... 10 Power Management Enhancements.........................................................................................
    [Show full text]
  • Lecture: Manycore GPU Architectures and Programming, Part 1
    Lecture: Manycore GPU Architectures and Programming, Part 1 CSCE 569 Parallel Computing Department of Computer Science and Engineering Yonghong Yan [email protected] https://passlab.github.io/CSCE569/ 1 Manycore GPU Architectures and Programming: Outline • Introduction – GPU architectures, GPGPUs, and CUDA • GPU Execution model • CUDA Programming model • Working with Memory in CUDA – Global memory, shared and constant memory • Streams and concurrency • CUDA instruction intrinsic and library • Performance, profiling, debugging, and error handling • Directive-based high-level programming model – OpenACC and OpenMP 2 Computer Graphics GPU: Graphics Processing Unit 3 Graphics Processing Unit (GPU) Image: http://www.ntu.edu.sg/home/ehchua/programming/opengl/CG_BasicsTheory.html 4 Graphics Processing Unit (GPU) • Enriching user visual experience • Delivering energy-efficient computing • Unlocking potentials of complex apps • Enabling Deeper scientific discovery 5 What is GPU Today? • It is a processor optimized for 2D/3D graphics, video, visual computing, and display. • It is highly parallel, highly multithreaded multiprocessor optimized for visual computing. • It provide real-time visual interaction with computed objects via graphics images, and video. • It serves as both a programmable graphics processor and a scalable parallel computing platform. – Heterogeneous systems: combine a GPU with a CPU • It is called as Many-core 6 Graphics Processing Units (GPUs): Brief History GPU Computing General-purpose computing on graphics processing units (GPGPUs) GPUs with programmable shading Nvidia GeForce GE 3 (2001) with programmable shading DirectX graphics API OpenGL graphics API Hardware-accelerated 3D graphics S3 graphics cards- single chip 2D accelerator Atari 8-bit computer IBM PC Professional Playstation text/graphics chip Graphics Controller card 1970 1980 1990 2000 2010 Source of information http://en.wikipedia.org/wiki/Graphics_Processing_Unit 7 NVIDIA Products • NVIDIA Corp.
    [Show full text]
  • Release 343 Graphics Drivers for Windows, Version 344.48. RN
    Release 343 Graphics Drivers for Windows - Version 344.48 RN-W34448-01v02 | September 22, 2014 Windows Vista / Windows 7 / Windows 8 / Windows 8.1 Release Notes TABLE OF CONTENTS 1 Introduction to Release Notes ................................................... 1 Structure of the Document ........................................................ 1 Changes in this Edition ............................................................. 1 2 Release 343 Driver Changes ..................................................... 2 Version 344.48 Highlights .......................................................... 2 What’s New in Version 344.48 ................................................. 3 What’s New in Release 343..................................................... 5 Limitations in This Release ..................................................... 8 Advanced Driver Information ................................................. 10 Changes and Fixed Issues in Version 344.48.................................... 14 Open Issues in Version 344.48.................................................... 15 Windows Vista/Windows 7 32-bit Issues..................................... 15 Windows Vista/Windows 7 64-bit Issues..................................... 15 Windows 8 32-bit Issues........................................................ 17 Windows 8 64-bit Issues........................................................ 17 Windows 8.1 Issues ............................................................. 18 Not NVIDIA Issues..................................................................
    [Show full text]
  • Cuda-Gdb Cuda Debugger
    CUDA-GDB CUDA DEBUGGER DU-05227-042 _v5.0 | October 2012 User Manual TABLE OF CONTENTS Chapter 1. Introduction.........................................................................................1 1.1 What is CUDA-GDB?...................................................................................... 1 1.2 Supported Features...................................................................................... 1 1.3 About This Document.................................................................................... 2 Chapter 2. Release Notes...................................................................................... 3 Chapter 3. Getting Started.....................................................................................6 3.1 Installation Instructions..................................................................................6 3.2 Setting Up the Debugger Environment................................................................6 3.2.1 Linux...................................................................................................6 3.2.2 Mac OS X............................................................................................. 6 3.2.3 Temporary Directory................................................................................ 7 3.3 Compiling the Application...............................................................................8 3.3.1 Debug Compilation.................................................................................. 8 3.3.2 Compiling for Fermi GPUs........................................................................
    [Show full text]