DRAFT - DATED MATERIAL the CONTENTS of THIS REVIEWER’S GUIDE IS INTENDED SOLELY for REFERENCE WHEN REVIEWING Rev a VERSIONS of VOODOO5 5500 REFERENCE BOARDS
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Scalability of Terrain Visualization in Large Virtual Environments
WORDT ' Facultyof Mathematics and Natural Department of NIET UITGELEEND Mathematics and Computing Science Scalability of Terrain Visualization in Large Virtual Environments Esger G.N. Abbink Advisors: dr. J.B.TM. Roerdink Department of Mathematics and Computing Science University of Groningen drs. M.J.B. van Delden drs. M. Wierda Virtual Environments, Systems, and Consultancy Zeegse .(,-,-, June,2000 Rkunlv,,,IOIOi*S DDothk W1s*ud. 'iMP* IRS&SIICSIWI'U :.'von S r-;tus800 9' Avr')1rs.r Scalability of terrain visualization in large Virtual Environments Esger G.N. Abbink Department of Mathematics and Computing Science Graduate specialization High Performance Computing and Imaging Studentnumber 0831425 Gerkesklooster/ Zeegse, April 2000 Rapport vesc WR-2000/3 •1 Table of Contents Scalability of terrain visualization in large Virtual Environments..1 1. Introduction 4 2. Virtual Environments 6 2.1 Startingpoints 6 2.2 Means-end analysis 6 2.3 Man-in-the-loop 6 2.4 Hardware 8 2.5 Real-world simulators 9 2.5.1 Flight Simulators 9 2.5.2 Driving Simulators 9 2.5.3 Rail vehicle simulators 10 2.5.4 Ship Simulator 11 2.5.5 yE Walkthrough 11 2.5.6 Entertainment Simulators 12 2.5.7 Telepresence 12 2.5.8 Virtual GIS 13 2.6 Summary & practical continuation 13 3. Scalable terrain visualization 15 3.1 Introduction 15 3.2 The sample implementation 15 3.2.1 Introduction 15 3.2.2 Getting it to work 15 3.2.3 Porting the sample implementation to 4Space 16 3.3 Design 16 3.3.1 Goal 16 3.3.2 Requirements 16 3.3.3 Terrain representation 16 3.3.4 Basic setup 18 3.3.5 Tessellation algorithm 19 3.3.6 Implementation approach 23 3.4 Implementation 24 3.4.1 Terrain data generation 24 3.4.2 Implementing Central Differencing 24 3.4.2 Interfacing 4Space 28 3.4.3 Memory management 29 3.4.4 Dynamic data storages 30 3.4.4.1 Queue 30 3.4.4.2 Dynamic List & Pool 31 3.4.4.3 Red-Black Tree 31 3.4.4.4 Dynamic Storage 32 3.4.4.5 Evaluating performance 33 2 4. -
Mobile 3D Devices They're Not Little
Mobile 3D Devices -- They’re not little PCs! Stephen Wilkinson – Graphics Software Technical Lead Texas Instruments CSSD/OMAP Who is this guy? ! Involved with simulation and games since 1995 ! Worked on SIMNET for the US Army ! PC gaming ! Titles include WarBirds 1 & 2, Fighter Squadron, AMA SuperBike, NHRA Drag Racing, NHRA Main Event ! 30+ Casino Games (yeah, yeah) ! Worked on core technology for several console games ! D&D Heroes, Mission Impossible: Operation SURMA, and T3: Redemption (NGC, PS2, Xbox) ! Former member of the Graphics and Computer Vision group at Nokia Research Center ! Now the CSSD graphics software technical lead at Texas Instruments working on OMAP Introduction ! Mobile 3D hardware is not a “Mini-me” of your desktop PC. ! To obtain similar features and relatively high levels of performance, mobile hardware has made some tradeoffs compared to the power of your desktop Introduction… ! If you are just learning mobile 3D or have learned about graphics and performance on a more “traditional” platform such as a PC or console, this presentation should help you: ! Recognize the most important areas in mobile power and performance for 3D and game development ! Take appropriate lessons learned from desktop development whenever possible… ! Avoid lessons from the desktop which can make your game slower or more power-hungry than it could be! Mobile performance preview ! Some you know, some you may not… Sorted by acronym the main problems are: ! CPU ! GPU ! Memory ! Your game The Mobile CPU ! No, it doesn’t have a Hemi. The Mobile GPU ! No, there’s not really a tiny 3dfx Voodoo™ card in that handset Mobile Memory ! It’s SLOOOOOOOW…. -
AMD Radeon E8860
Components for AMD’s Embedded Radeon™ E8860 GPU INTRODUCTION The E8860 Embedded Radeon GPU available from CoreAVI is comprised of temperature screened GPUs, safety certi- fiable OpenGL®-based drivers, and safety certifiable GPU tools which have been pre-integrated and validated together to significantly de-risk the challenges typically faced when integrating hardware and software components. The plat- form is an off-the-shelf foundation upon which safety certifiable applications can be built with confidence. Figure 1: CoreAVI Support for E8860 GPU EXTENDED TEMPERATURE RANGE CoreAVI provides extended temperature versions of the E8860 GPU to facilitate its use in rugged embedded applications. CoreAVI functionally tests the E8860 over -40C Tj to +105 Tj, increasing the manufacturing yield for hardware suppliers while reducing supply delays to end customers. coreavi.com [email protected] Revision - 13Nov2020 1 E8860 GPU LONG TERM SUPPLY AND SUPPORT CoreAVI has provided consistent and dedicated support for the supply and use of the AMD embedded GPUs within the rugged Mil/Aero/Avionics market segment for over a decade. With the E8860, CoreAVI will continue that focused support to ensure that the software, hardware and long-life support are provided to meet the needs of customers’ system life cy- cles. CoreAVI has extensive environmentally controlled storage facilities which are used to store the GPUs supplied to the Mil/ Aero/Avionics marketplace, ensuring that a ready supply is available for the duration of any program. CoreAVI also provides the post Last Time Buy storage of GPUs and is often able to provide additional quantities of com- ponents when COTS hardware partners receive increased volume for existing products / systems requiring additional inventory. -
John Carmack Archive - .Plan (1998)
John Carmack Archive - .plan (1998) http://www.team5150.com/~andrew/carmack March 18, 2007 Contents 1 January 5 1.1 Some of the things I have changed recently (Jan 01, 1998) . 5 1.2 Jan 02, 1998 ............................ 6 1.3 New stuff fixed (Jan 03, 1998) ................. 7 1.4 Version 3.10 patch is now out. (Jan 04, 1998) ......... 8 1.5 Jan 09, 1998 ............................ 9 1.6 I AM GOING OUT OF TOWN NEXT WEEK, DON’T SEND ME ANY MAIL! (Jan 11, 1998) ................. 10 2 February 12 2.1 Ok, I’m overdue for an update. (Feb 04, 1998) ........ 12 2.2 Just got back from the Q2 wrap party in vegas that Activi- sion threw for us. (Feb 09, 1998) ................ 14 2.3 Feb 12, 1998 ........................... 15 2.4 8 mb or 12 mb voodoo 2? (Feb 16, 1998) ........... 19 2.5 I just read the Wired article about all the Doom spawn. (Feb 17, 1998) .......................... 20 2.6 Feb 22, 1998 ........................... 21 1 John Carmack Archive 2 .plan 1998 3 March 22 3.1 American McGee has been let go from Id. (Mar 12, 1998) . 22 3.2 The Old Plan (Mar 13, 1998) .................. 22 3.3 Mar 20, 1998 ........................... 25 3.4 I just shut down the last of the NEXTSTEP systems running at id. (Mar 21, 1998) ....................... 26 3.5 Mar 26, 1998 ........................... 28 4 April 30 4.1 Drag strip day! (Apr 02, 1998) ................. 30 4.2 Things are progressing reasonably well on the Quake 3 en- gine. (Apr 08, 1998) ....................... 31 4.3 Apr 16, 1998 .......................... -
Rasterized Cnlor
US006825851B1 (12) United States Patent (10) Patent N0.: US 6,825,851 B1 Leather (45) Date of Patent: Nov. 30, 2004 (54) METHOD AND APPARATUS FOR (74) Attorney, Agent, or Firm—Nixon & Vanderhye PC ENVIRONMENT-MAPPED BUMP-MAPPING IN A GRAPHICS SYSTEM (57) ABSTRACT (75) Inventor: Mark M. Leather, Saratoga, CA (US) A graphics system including a custom graphics and audio (73) Assignee: Nintendo Co., Ltd., Kyoto (JP) processor produces exciting 2D and 3D graphics and sur round sound. The system includes a graphics and audio ( * ) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 processor including a 3D graphics pipeline and an audio U.S.C. 154(b) by 369 days. digital signal processor. Realistic looking surfaces on ren dered images are generated by EMBM using an indirect (21) Appl. No.: 09/722,381 texture lookup to a “bump map” followed by an environ (22) Filed: Nov. 28, 2000 ment or light mapping. Apparatus and example methods for Related US. Application Data environment-mapped style of bump-mapping (EMBM) are (60) Provisional application No. 60/226,893, ?led on Aug. 23, provided that use a pre-completed bump-map texture 2000. accessed as an indirect texture along With pre-computed (51) Int. Cl.7 ......................... .. G09G 5/00; G06T 15/60 object surface normals (i.e., the Normal, Tangent and Binor (52) US. Cl. ..................... .. 345/584; 345/581; 345/426; 345/848 mal vectors) from each vertex of rendered polygons to (58) Field of Search ....................... .. 345/426, 581—582, effectively generate a neW perturbed Normal vector per 345/584, 501, 506, 427, 522, 848 vertex. -
3Dfx Oral History Panel Gordon Campbell, Scott Sellers, Ross Q. Smith, and Gary M. Tarolli
3dfx Oral History Panel Gordon Campbell, Scott Sellers, Ross Q. Smith, and Gary M. Tarolli Interviewed by: Shayne Hodge Recorded: July 29, 2013 Mountain View, California CHM Reference number: X6887.2013 © 2013 Computer History Museum 3dfx Oral History Panel Shayne Hodge: OK. My name is Shayne Hodge. This is July 29, 2013 at the afternoon in the Computer History Museum. We have with us today the founders of 3dfx, a graphics company from the 1990s of considerable influence. From left to right on the camera-- I'll let you guys introduce yourselves. Gary Tarolli: I'm Gary Tarolli. Scott Sellers: I'm Scott Sellers. Ross Smith: Ross Smith. Gordon Campbell: And Gordon Campbell. Hodge: And so why don't each of you take about a minute or two and describe your lives roughly up to the point where you need to say 3dfx to continue describing them. Tarolli: All right. Where do you want us to start? Hodge: Birth. Tarolli: Birth. Oh, born in New York, grew up in rural New York. Had a pretty uneventful childhood, but excelled at math and science. So I went to school for math at RPI [Rensselaer Polytechnic Institute] in Troy, New York. And there is where I met my first computer, a good old IBM mainframe that we were just talking about before [this taping], with punch cards. So I wrote my first computer program there and sort of fell in love with computer. So I became a computer scientist really. So I took all their computer science courses, went on to Caltech for VLSI engineering, which is where I met some people that influenced my career life afterwards. -
Efficient Algorithms for Large-Scale Image Analysis
Efficient Algorithms for Large-Scale Image Analysis zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften der Fakultät für Informatik des Karlsruher Instituts für Technologie genehmigte Dissertation von Jan Wassenberg aus Koblenz Tag der mündlichen Prüfung: 24. Oktober 2011 Erster Gutachter: Prof. Dr. Peter Sanders Zweiter Gutachter: Prof. Dr.-Ing. Jürgen Beyerer Abstract The past decade has seen major improvements in the capabilities and availability of imaging sensor systems. Commercial satellites routinely provide panchromatic images with sub-meter resolution. Airborne line scanner cameras yield multi-spectral data with a ground sample distance of 5 cm. The resulting overabundance of data brings with it the challenge of timely analysis. Fully auto- mated processing still appears infeasible, but an intermediate step might involve a computer-assisted search for interesting objects. This would reduce the amount of data for an analyst to examine, but remains a challenge in terms of processing speed and working memory. This work begins by discussing the trade-offs among the various hardware architectures that might be brought to bear upon the problem. FPGA and GPU-based solutions are less universal and entail longer development cycles, hence the choice of commodity multi-core CPU architectures. Distributed processing on a cluster is deemed too costly. We will demonstrate the feasibility of processing aerial images of 100 km × 100 km areas at 1 m resolution within 2 hours on a single workstation with two processors and a total of twelve cores. Because existing approaches cannot cope with such amounts of data, each stage of the image processing pipeline – from data access and signal processing to object extraction and feature computation – will have to be designed from the ground up for maximum performance. -
12) United States Patent 10) Patent No.: US 7.003.588 B1
US007003588B1 12) United States Patent 10) Patent No.: US 7.003.5889 9 B1 Takeda et al. 45) Date of Patent: Feb. 21,5 2006 (54) PERIPHERAL DEVICES FOR A VIDEO 4,567,516 A 1/1986 Scherer et al. .............. 358/114 GAME SYSTEM 4,570,233 A. 2/1986 Yan et al. 4,589,089 A 5/1986 Frederiksen ................ 364/900 (75) Inventors: Genyo Takeda, Kyoto (JP), Ko Shiota, 4,592,012 A 5/1986 Braun ........................ 364/900 Kyoto- (JP);2 Munchitoe Oira,2 Kyoto- 4,725,831† A 2/19884/1987 Colemanº ºatoshi º Nishiumi, Kyoto sº (JP) (JP); 4,829,2954,799,635 A 5/19891/1989 HiroyukiNakagawa .................. 364/900 - e 4,837,488 A 6/1989 Donahue ..................... 324/66 (73) Assignee: Nintendo Co., Ltd., Kyoto (JP) 4,850,591. A 7/1989 Takezawa et al. ............ 273/85 (*) Notice: Subject to any disclaimer, the term of this (Continued) patent is extended or adjusted under 35 U.S.C. 154(b) by 0 days. FOREIGN PATENT DOCUMENTS CA 2070934 12/1993 (21) Appl. No.: 10/225,488 (Continued) (22) Filed: Aug. 22, 2002 OTHER PUBLICATIONS Related U.S. Application Data “Pinouts for Various Connectors in Real Life (tm)”, ?on (60) Provisional application No. 60/313,812, filed on Aug. line], retrieved from the Internet, http://repairfaq.ece.drex 22, 2001. el.edu/REPAIR/F, Pinoutsl.html, updated May 20, 1997 (per document). (51) Int. Cl. A63F I3/00 (2006.01) (Continued) (52) U.S. Cl. .............................. .."...º.º. Primary Examiner—Christopher Shin (58) Fielde of Classificatione e Search ................2 710/100,2 (74) Attorney, Agent, or Firm—Nixon & Vanderhye, P.C. -
Integrating Mali GPU with the Browser
Integrating Mali GPU with the Browser Wasim Abbas Staff Engineer, Mali Ecosystem 1 What’s Coming? § Introduction § Mali architecture § Optimizing for Mali § Common pitfalls § Questions 2 Introduction § Technical Lead of Middleware graphics team in Mali Ecosystem § Working with Skia, FireFox (Gecko) and WebKit teams (GPU acceleration for The Web) § Have worked with Mali content optimization and creation tools § Past expertise in the Game industry, engine development § Past expertise teaching Game engine architecture § Who are you? 3 Graphics in the Embedded World § Embedded / mobile graphics fundamentally different from PC § Not just a scaled down version of the desktop world § Completely different power and bandwidth budgets § No dedicated GPU memory or bus – all shared with CPU, video, DSP § Need to last days rather than hours on a single battery charge § Requires dedicated solutions § Must handle “PC use cases” with a mobile phone power budget § Maximize processing efficiency in an embedded memory subsystem 4 Optimizing for Mali § Understanding Mali architecture § Understanding your browser and underlying renderer § Understanding OpenGL ES API and what happens under the hood § Multi-level optimizations at system and application level § Optimizations at client level 5 Abstract Rendering Machine glDraw(1) glDraw(2) glDraw(3) eglSwapBuffers() Original article from Peter Harris at http://community.arm.com/groups/arm-mali-graphics/blog/2014/02/03/the-mali-gpu-an-abstract-machine-part-1 6 Abstract Rendering Machine Synchronous API, asynchronous -
Matrox in the New Millennium: Parhelia Reviewed Matrox in the New Millennium: Parhelia Reviewed by Brian Neal – July 2002
Ace’s Hardware Matrox in the New Millennium: Parhelia Reviewed Matrox in the New Millennium: Parhelia Reviewed By Brian Neal – July 2002 Introduction For some time following the introduction of the Matrox G400 and later the G450, we heard rumors about a "G800" project. About a year and a month ago, Matrox introduced the world to the G550. But the G550 lacked the performance and features of its competitors, and was relegated mostly to 2D work. The G550 was more an evolution of the G450 than anything else, but this time, things are different. Matrox's new Parhelia is an all-new design, incorporating modern features such as Direct X 8.1-compliant pixel and vertex shaders. The G550's 166 MHz 64-bit DDR SDRAM memory interface has been replaced with a far more robust 275 MHz (250 MHz OEM/bulk) 256-bit DDR SDRAM interface capable of 17.6 GB/s. This combined with some interesting and innovative features like hardware displacement-mapping, triple-head surround gaming, and the prospects for Matrox's next- generation product are looking quite good. The Matrox Parhelia But not everything is looking so bright for Parhelia. Manufactured on a 0.15µ process, the 80 million transistor GPU is quite large and also quite hot. Consequently, it currently clocks in at only 220 MHz. To contrast, compare the GeForce 4 Ti4400's 300 MHz clockrate. The low clockrate is compounded by a lack of hardware occlusion culling, which means the quad-pipeline renderer is significantly less efficient than many other contemporary designs when it comes to overdraw. -
Linux Hardware Compatibility HOWTO
Linux Hardware Compatibility HOWTO Steven Pritchard Southern Illinois Linux Users Group / K&S Pritchard Enterprises, Inc. <[email protected]> 3.2.4 Copyright © 2001−2007 Steven Pritchard Copyright © 1997−1999 Patrick Reijnen 2007−05−22 This document attempts to list most of the hardware known to be either supported or unsupported under Linux. Copyright This HOWTO is free documentation; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free software Foundation; either version 2 of the license, or (at your option) any later version. Linux Hardware Compatibility HOWTO Table of Contents 1. Introduction.....................................................................................................................................................1 1.1. Notes on binary−only drivers...........................................................................................................1 1.2. Notes on proprietary drivers.............................................................................................................1 1.3. System architectures.........................................................................................................................1 1.4. Related sources of information.........................................................................................................2 1.5. Known problems with this document...............................................................................................2 1.6. New versions of this document.........................................................................................................2 -
Towards Left Duff S Mdbg Holt Winters Gai Incl Tax Drupal Fapi Icici
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