Appendix C Graphics and Computing Gpus
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An Algorithm for the Construction of Intrinsic Delaunay Triangulations with Applications to Digital Geometry Processing
An Algorithm for the Construction of Intrinsic Delaunay Triangulations with Applications to Digital Geometry Processing Matthew Fisher Boris Springborn Peter Schroder¨ Alexander I. Bobenko Caltech TU Berlin Caltech TU Berlin Abstract The discrete Laplace-Beltrami operator plays a prominent role in many Digital Geometry Processing applications ranging from de- noising to parameterization, editing, and physical simulation. The standard discretization uses the cotangents of the angles in the im- mersed mesh which leads to a variety of numerical problems. We advocate the use of the intrinsic Laplace-Beltrami operator. It sat- isfies a local maximum principle, guaranteeing, e.g., that no flipped triangles can occur in parameterizations. It also leads to better con- ditioned linear systems. The intrinsic Laplace-Beltrami operator is based on an intrinsic Delaunay triangulation of the surface. We detail an incremental algorithm to construct such triangulations to- gether with an overlay structure which captures the relationship be- tween the extrinsic and intrinsic triangulations. Using a variety of example meshes we demonstrate the numerical benefits of the in- trinsic Laplace-Beltrami operator. Figure 1: Left: carrier of the (cat head) surface as defined by the original embedded mesh. Right: the intrinsic Delaunay triangu- 1 Introduction lation of the same carrier. Delaunay edges which appear in the original triangulation are shown in white. Some of the original 2 Delaunay triangulations of domains in R play an important role edges are not present anymore (these are shown in black). In their in many numerical computing applications because of the quality stead we see red edges which appear as the result of intrinsic flip- guarantees they make, such as: among all triangulations of the con- ping. -
The Road Ahead for Computing Systems
56 JANUARY 2019 HiPEAC conference 2019 The road ahead for Valencia computing systems Monica Lam on keeping the web open Alberto Sangiovanni Vincentelli on building tech businesses Koen Bertels on quantum computing Tech talk 2030 contents 7 14 16 Benvinguts a València Monica Lam on open-source Starting and scaling a successful voice assistants tech business 3 Welcome 30 SME snapshot Koen De Bosschere UltraSoC: Smarter systems thanks to self-aware chips 4 Policy corner Rupert Baines The future of technology – looking into the crystal ball 33 Innovation Europe Sandro D’Elia M2DC: The future of modular microserver technology 6 News João Pita Costa, Ariel Oleksiak, Micha vor dem Berge and Mario Porrmann 14 HiPEAC voices 34 Innovation Europe ‘We are witnessing the creation of closed, proprietary TULIPP: High-performance image processing for linguistic webs’ embedded computers Monica Lam Philippe Millet, Diana Göhringer, Michael Grinberg, 16 HiPEAC voices Igor Tchouchenkov, Magnus Jahre, Magnus Peterson, ‘Do not think that SME status is the final game’ Ben Rodriguez, Flemming Christensen and Fabien Marty Alberto Sangiovanni Vincentelli 35 Innovation Europe 18 Technology 2030 Software for the big data era with E2Data Computing for the future? The way forward for Juan Fumero computing systems 36 Innovation Europe Marc Duranton, Madeleine Gray and Marcin Ostasz A RECIPE for HPC success 23 Technology 2030 William Fornaciari Tech talk 2030 37 Innovation Europe Solving heterogeneous challenges with the 24 Future compute special Heterogeneity Alliance -
(12) United States Patent (10) Patent No.: US 7,133,041 B2 Kaufman Et Al
US007133041B2 (12) United States Patent (10) Patent No.: US 7,133,041 B2 Kaufman et al. (45) Date of Patent: Nov. 7, 2006 (54) APPARATUS AND METHOD FOR VOLUME (56) References Cited PROCESSING AND RENDERING U.S. PATENT DOCUMENTS (75) Inventors: Arie E. Kaufman, Plainview, NY (US); 4,314,351 A 2f1982 Postel et al. Ingmar Bitter, Lake Grove, NY (US); 4,371,933 A 2, 1983 Bresenham et al. Frank Dachille, Amityville, NY (US); Kevin Kreeger, East Setauket, NY (Continued) (US); Baoquan Chen, Maple Grove, FOREIGN PATENT DOCUMENTS MN (US) EP O 216 156 A2 4f1987 (73) Assignee: The Research Foundation of State University of New York, Albany, NY (Continued) (US) OTHER PUBLICATIONS (*) Notice: Subject to any disclaimer, the term of this Knittel, G., TriangleCaster: extensions to 3D-texturing units for patent is extended or adjusted under 35 accelerated volume rendering, 1999, Proceedings of the ACM U.S.C. 154(b) by 742 days. SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware, pp. 25-34.* (21) Appl. No.: 10/204,685 (Continued) PCT Fed: Feb. 26, 2001 (22) Primary Examiner Ulka Chauhan (86) PCT No.: PCT/USO1 (O6345 Assistant Examiner Said Broome (74) Attorney, Agent, or Firm Hoffmann & Baron, LLP S 371 (c)(1), (2), (4) Date: Jan. 9, 2003 (57) ABSTRACT (87) PCT Pub. No.: WOO1A63561 An apparatus and method for real-time Volume processing and universal three-dimensional rendering. The apparatus PCT Pub. Date: Aug. 30, 2001 includes a plurality of three-dimensional (3D) memory units; at least one pixel bus for providing global horizontal (65) Prior Publication Data communication; a plurality of rendering pipelines; at least one geometry bus; and a control unit. -
Fog Computing: a Platform for Internet of Things and Analytics
Fog Computing: A Platform for Internet of Things and Analytics Flavio Bonomi, Rodolfo Milito, Preethi Natarajan and Jiang Zhu Abstract Internet of Things (IoT) brings more than an explosive proliferation of endpoints. It is disruptive in several ways. In this chapter we examine those disrup- tions, and propose a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing. In particular, we pay attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge. 1 Introduction The “pay-as-you-go” Cloud Computing model is an efficient alternative to owning and managing private data centers (DCs) for customers facing Web applications and batch processing. Several factors contribute to the economy of scale of mega DCs: higher predictability of massive aggregation, which allows higher utilization with- out degrading performance; convenient location that takes advantage of inexpensive power; and lower OPEX achieved through the deployment of homogeneous compute, storage, and networking components. Cloud computing frees the enterprise and the end user from the specification of many details. This bliss becomes a problem for latency-sensitive applications, which require nodes in the vicinity to meet their delay requirements. An emerging wave of Internet deployments, most notably the Internet of Things (IoTs), requires mobility support and geo-distribution in addition to location awareness and low latency. We argue that a new platform is needed to meet these requirements; a platform we call Fog Computing [1]. We also claim that rather than cannibalizing Cloud Computing, F. Bonomi R. -
Opengl Distilled / Paul Martz
Page left blank intently OpenGL® Distilled By Paul Martz ............................................... Publisher: Addison Wesley Professional Pub Date: February 27, 2006 Print ISBN-10: 0-321-33679-8 Print ISBN-13: 978-0-321-33679-8 Pages: 304 Table of Contents | Inde OpenGL opens the door to the world of high-quality, high-performance 3D computer graphics. The preferred application programming interface for developing 3D applications, OpenGL is widely used in video game development, visuali,ation and simulation, CAD, virtual reality, modeling, and computer-generated animation. OpenGL® Distilled provides the fundamental information you need to start programming 3D graphics, from setting up an OpenGL development environment to creating realistic te tures and shadows. .ritten in an engaging, easy-to-follow style, this boo/ ma/es it easy to find the information you0re loo/ing for. 1ou0ll quic/ly learn the essential and most-often-used features of OpenGL 2.0, along with the best coding practices and troubleshooting tips. Topics include Drawing and rendering geometric data such as points, lines, and polygons Controlling color and lighting to create elegant graphics Creating and orienting views Increasing image realism with te ture mapping and shadows Improving rendering performance Preserving graphics integrity across platforms A companion .eb site includes complete source code e amples, color versions of special effects described in the boo/, and additional resources. Page left blank intently Table of contents: Chapter 6. Texture Mapping Copyright ............................................................... 4 Section 6.1. Using Texture Maps ........................... 138 Foreword ............................................................... 6 Section 6.2. Lighting and Shadows with Texture .. 155 Preface ................................................................... 7 Section 6.3. Debugging .......................................... 169 About the Book .................................................... -
Powervr SGX Series5xt IP Core Family
PowerVR SGX Series5XT IP Core Family The PowerVR™ SGX Series5XT Graphics Processing Unit (GPU) IP core family is a series Features of highly efficient graphics acceleration IP cores that meet the multimedia requirements of • Most comprehensive IP core family the next generation of consumer, communications and computing applications. and roadmap in the industry PowerVR SGX Series5XT architecture is fully scalable for a wide range of area and • USSE2 delivers twice the peak performance requirements, enabling it to target markets from low cost feature-rich mobile floating point and instruction multimedia products to very high performance consoles and computing devices. throughput of Series5 USSE • YUV and colour space accelerators The family incorporates the second-generation Universal Scalable Shader Engine (USSE2™), for improved performance with a feature set that exceeds the requirements of OpenGL 2.0 and Microsoft Shader • Upgraded PowerVR Series5XT Model 3, enabling 2D, 3D and general purpose (GP-GPU) processing in a single core. shader-driven tile-based deferred rendering (TBDR) architecture • Multi-processor options enable scalability to higher performance • Support for all industry standard PowerVR SGX Family mobile and desktop graphics APIs and operating sytems Series5XT SGX543MP1-16, SGX544MP1-16, SGX554MP1-16 • Fully backwards compatible with PowerVR MBX and SGX Series5 Series5 SGX520, SGX530, SGX531, SGX535, SGX540, SGX545 Benefits Multi-standard API and OS • Extensive product line supports all area/performance requirements OpenGL -
AMD Accelerated Parallel Processing Opencl Programming Guide
AMD Accelerated Parallel Processing OpenCL Programming Guide November 2013 rev2.7 © 2013 Advanced Micro Devices, Inc. All rights reserved. AMD, the AMD Arrow logo, AMD Accelerated Parallel Processing, the AMD Accelerated Parallel Processing logo, ATI, the ATI logo, Radeon, FireStream, FirePro, Catalyst, and combinations thereof are trade- marks of Advanced Micro Devices, Inc. Microsoft, Visual Studio, Windows, and Windows Vista are registered trademarks of Microsoft Corporation in the U.S. and/or other jurisdic- tions. Other names are for informational purposes only and may be trademarks of their respective owners. OpenCL and the OpenCL logo are trademarks of Apple Inc. used by permission by Khronos. The contents of this document are provided in connection with Advanced Micro Devices, Inc. (“AMD”) products. AMD makes no representations or warranties with respect to the accuracy or completeness of the contents of this publication and reserves the right to make changes to specifications and product descriptions at any time without notice. The information contained herein may be of a preliminary or advance nature and is subject to change without notice. No license, whether express, implied, arising by estoppel or other- wise, to any intellectual property rights is granted by this publication. Except as set forth in AMD’s Standard Terms and Conditions of Sale, AMD assumes no liability whatsoever, and disclaims any express or implied warranty, relating to its products including, but not limited to, the implied warranty of merchantability, fitness for a particular purpose, or infringement of any intellectual property right. AMD’s products are not designed, intended, authorized or warranted for use as compo- nents in systems intended for surgical implant into the body, or in other applications intended to support or sustain life, or in any other application in which the failure of AMD’s product could create a situation where personal injury, death, or severe property or envi- ronmental damage may occur. -
Real-Time Graphics Architecture P
4/18/2007 Real-Time Graphics Architecture Lecture 4: Parallelism and Communication Kurt Akeley Pat Hanrahan http://graphics.stanford.edu/cs448-07-spring/ CS448 Lecture 4 Kurt Akeley, Pat Hanrahan, Spring 2007 Topics 1. Frame buffers 2. Types of parallelism 3. Communication patterns and requirements 4. Sorting classification for parallel rendering (with examples) CS448 Lecture 4 Kurt Akeley, Pat Hanrahan, Spring 2007 1 4/18/2007 Frame Buffers Raster vs. calligraphic Raster (image order) dominant choice Calligraphic (object order) Earliest choice (Sketchpad) E&S terminals in the 70s and 80s Works with light pens Scene complexity affects frame rate Monitors are expensive Still required for FAA simulation Increases absolute brightness of light points CS448 Lecture 4 Kurt Akeley, Pat Hanrahan, Spring 2007 2 4/18/2007 Frame buffer definitions What is a frame buffer? What can we learn by considering different definitions? CS448 Lecture 4 Kurt Akeley, Pat Hanrahan, Spring 2007 Frame buffer definition #1 Storage for commands that are executed to refresh the display Allows for raster or calligraphiccalligraphic display (e. g. Megatech) “Frame buffer” for calligraphic display is a “display list” OpenGL “render list”? Key point: frame buffer contents are interpreted Color mapping Image scaling, warping Window system (overlay, separate windows, …) Address Recalculation Pipeline CS448 Lecture 4 Kurt Akeley, Pat Hanrahan, Spring 2007 3 4/18/2007 Frame buffer definition #2 Image memory used to decouple the render frame rate from the display -
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Case M:07-cv-01826-WHA Document 249 Filed 11/08/2007 Page 1 of 34 1 BOIES, SCHILLER & FLEXNER LLP WILLIAM A. ISAACSON (pro hac vice) 2 5301 Wisconsin Ave. NW, Suite 800 Washington, D.C. 20015 3 Telephone: (202) 237-2727 Facsimile: (202) 237-6131 4 Email: [email protected] 5 6 BOIES, SCHILLER & FLEXNER LLP BOIES, SCHILLER & FLEXNER LLP JOHN F. COVE, JR. (CA Bar No. 212213) PHILIP J. IOVIENO (pro hac vice) 7 DAVID W. SHAPIRO (CA Bar No. 219265) ANNE M. NARDACCI (pro hac vice) KEVIN J. BARRY (CA Bar No. 229748) 10 North Pearl Street 8 1999 Harrison St., Suite 900 4th Floor Oakland, CA 94612 Albany, NY 12207 9 Telephone: (510) 874-1000 Telephone: (518) 434-0600 Facsimile: (510) 874-1460 Facsimile: (518) 434-0665 10 Email: [email protected] Email: [email protected] [email protected] [email protected] 11 [email protected] 12 Attorneys for Plaintiff Jordan Walker Interim Class Counsel for Direct Purchaser 13 Plaintiffs 14 15 UNITED STATES DISTRICT COURT 16 NORTHERN DISTRICT OF CALIFORNIA 17 18 IN RE GRAPHICS PROCESSING UNITS ) Case No.: M:07-CV-01826-WHA ANTITRUST LITIGATION ) 19 ) MDL No. 1826 ) 20 This Document Relates to: ) THIRD CONSOLIDATED AND ALL DIRECT PURCHASER ACTIONS ) AMENDED CLASS ACTION 21 ) COMPLAINT FOR VIOLATION OF ) SECTION 1 OF THE SHERMAN ACT, 15 22 ) U.S.C. § 1 23 ) ) 24 ) ) JURY TRIAL DEMANDED 25 ) ) 26 ) ) 27 ) 28 THIRD CONSOLIDATED AND AMENDED CLASS ACTION COMPLAINT BY DIRECT PURCHASERS M:07-CV-01826-WHA Case M:07-cv-01826-WHA Document 249 Filed 11/08/2007 Page 2 of 34 1 Plaintiffs Jordan Walker, Michael Bensignor, d/b/a Mike’s Computer Services, Fred 2 Williams, and Karol Juskiewicz, on behalf of themselves and all others similarly situated in the 3 United States, bring this action for damages and injunctive relief under the federal antitrust laws 4 against Defendants named herein, demanding trial by jury, and complaining and alleging as 5 follows: 6 NATURE OF THE CASE 7 1. -
SIMD Extensions
SIMD Extensions PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 12 May 2012 17:14:46 UTC Contents Articles SIMD 1 MMX (instruction set) 6 3DNow! 8 Streaming SIMD Extensions 12 SSE2 16 SSE3 18 SSSE3 20 SSE4 22 SSE5 26 Advanced Vector Extensions 28 CVT16 instruction set 31 XOP instruction set 31 References Article Sources and Contributors 33 Image Sources, Licenses and Contributors 34 Article Licenses License 35 SIMD 1 SIMD Single instruction Multiple instruction Single data SISD MISD Multiple data SIMD MIMD Single instruction, multiple data (SIMD), is a class of parallel computers in Flynn's taxonomy. It describes computers with multiple processing elements that perform the same operation on multiple data simultaneously. Thus, such machines exploit data level parallelism. History The first use of SIMD instructions was in vector supercomputers of the early 1970s such as the CDC Star-100 and the Texas Instruments ASC, which could operate on a vector of data with a single instruction. Vector processing was especially popularized by Cray in the 1970s and 1980s. Vector-processing architectures are now considered separate from SIMD machines, based on the fact that vector machines processed the vectors one word at a time through pipelined processors (though still based on a single instruction), whereas modern SIMD machines process all elements of the vector simultaneously.[1] The first era of modern SIMD machines was characterized by massively parallel processing-style supercomputers such as the Thinking Machines CM-1 and CM-2. These machines had many limited-functionality processors that would work in parallel. -
Driver Riva Tnt2 64
Driver riva tnt2 64 click here to download The following products are supported by the drivers: TNT2 TNT2 Pro TNT2 Ultra TNT2 Model 64 (M64) TNT2 Model 64 (M64) Pro Vanta Vanta LT GeForce. The NVIDIA TNT2™ was the first chipset to offer a bit frame buffer for better quality visuals at higher resolutions, bit color for TNT2 M64 Memory Speed. NVIDIA no longer provides hardware or software support for the NVIDIA Riva TNT GPU. The last Forceware unified display driver which. version now. NVIDIA RIVA TNT2 Model 64/Model 64 Pro is the first family of high performance. Drivers > Video & Graphic Cards. Feedback. NVIDIA RIVA TNT2 Model 64/Model 64 Pro: The first chipset to offer a bit frame buffer for better quality visuals Subcategory, Video Drivers. Update your computer's drivers using DriverMax, the free driver update tool - Display Adapters - NVIDIA - NVIDIA RIVA TNT2 Model 64/Model 64 Pro Computer. (In Windows 7 RC1 there was the build in TNT2 drivers). http://kemovitra. www.doorway.ru Use the links on this page to download the latest version of NVIDIA RIVA TNT2 Model 64/Model 64 Pro (Microsoft Corporation) drivers. All drivers available for. NVIDIA RIVA TNT2 Model 64/Model 64 Pro - Driver Download. Updating your drivers with Driver Alert can help your computer in a number of ways. From adding. Nvidia RIVA TNT2 M64 specs and specifications. Price comparisons for the Nvidia RIVA TNT2 M64 and also where to download RIVA TNT2 M64 drivers. Windows 7 and Windows Vista both fail to recognize the Nvidia Riva TNT2 ( Model64/Model 64 Pro) which means you are restricted to a low. -
Geometry-Aware Topological Decompositions of Meshes
UC Irvine UC Irvine Electronic Theses and Dissertations Title Geometry-aware topological decompositions of meshes Permalink https://escholarship.org/uc/item/3vh0q7wn Author Chen, Jia Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, IRVINE Geometry-aware topological decompositions of meshes DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Computer Science by Jia Chen Dissertation Committee: Professor Gopi Meenakshisundaram, Chair Professor Aditi Majumder Professor Shuang Zhao 2019 Chapter3 c 2016 ACM New York, NY, USA Chapter3 c 2018 ACM New York, NY, USA All other materials c 2019 Jia Chen DEDICATION To my family \. a man who keeps company with glaciers comes to feel tolerably insignificant by and by." { Mark Twain, A Tramp Abroad ii TABLE OF CONTENTS Page LIST OF FIGURESv LIST OF TABLESx LIST OF ALGORITHMS xi ACKNOWLEDGMENTS xii CURRICULUM VITAE xiii ABSTRACT OF THE DISSERTATION xiv 1 Introduction1 1.1 Cycles of topological properties.........................2 1.2 Topological decompositions of meshes......................4 2 Definitions and Background7 2.1 Surfaces and their topological classification...................7 2.2 Primal graph and dual graph embedded on a surface.............8 2.3 Paths and cycles.................................9 2.4 Tunnel and handle cycles............................. 11 3 Iterative localization of handle and tunnel cycles 13 3.1 Related work................................... 14 3.2 Problem formulation............................... 15 3.3 Localizing handle and tunnel cycles....................... 16 3.3.1 Iterative tree-cotree algorithm...................... 16 3.3.2 Cycle tightening.............................. 20 3.3.3 Decoupling composite fundamental cycles...............