An Automatic Multi-Platform Account Generation System
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
PACKET 7 BOOKSTORE 433 Lecture 5 Dr W IBM OVERVIEW
“PROCESSORS” and multi-processors Excerpt from Hennessey Computer Architecture book; edits by JT Wunderlich PhD Plus Dr W’s IBM Research & Development: JT Wunderlich PhD “PROCESSORS” Excerpt from Hennessey Computer Architecture book; edits by JT Wunderlich PhD Historical Perspective and Further 7.14 Reading There is a tremendous amount of history in multiprocessors; in this section we divide our discussion by both time period and architecture. We start with the SIMD SIMD=SinGle approach and the Illiac IV. We then turn to a short discussion of some other early experimental multiprocessors and progress to a discussion of some of the great Instruction, debates in parallel processing. Next we discuss the historical roots of the present multiprocessors and conclude by discussing recent advances. Multiple Data SIMD Computers: Attractive Idea, Many Attempts, No Lasting Successes The cost of a general multiprocessor is, however, very high and further design options were considered which would decrease the cost without seriously degrading the power or efficiency of the system. The options consist of recentralizing one of the three major components. Centralizing the [control unit] gives rise to the basic organization of [an] . array processor such as the Illiac IV. Bouknight, et al.[1972] The SIMD model was one of the earliest models of parallel computing, dating back to the first large-scale multiprocessor, the Illiac IV. The key idea in that multiprocessor, as in more recent SIMD multiprocessors, is to have a single instruc- tion that operates on many data items at once, using many functional units (see Figure 7.14.1). Although successful in pushing several technologies that proved useful in later projects, it failed as a computer. -
Online Sec 6.15.Indd
6.155.9 Historical Perspective and Further Reading Th ere is a tremendous amount of history in multiprocessors; in this section we divide our discussion by both time period and architecture. We start with the SIMD approach and the Illiac IV. We then turn to a short discussion of some other early experimental multiprocessors and progress to a discussion of some of the great debates in parallel processing. Next we discuss the historical roots of the present multiprocessors and conclude by discussing recent advances. SIMD Computers: Attractive Idea, Many Attempts, No Lasting Successes Th e cost of a general multiprocessor is, however, very high and further design options were considered which would decrease the cost without seriously degrading the power or effi ciency of the system. Th e options consist of recentralizing one of the three major components. Centralizing the [control unit] gives rise to the basic organization of [an] . array processor such as the Illiac IV. Bouknight et al. [1972] Th e SIMD model was one of the earliest models of parallel computing, dating back to the fi rst large-scale multiprocessor, the Illiac IV. Th e key idea in that multiprocessor, as in more recent SIMD multiprocessors, is to have a single instruction that operates on many data items at once, using many functional units (see Figure 6.15.1). Although successful in pushing several technologies that proved useful in later projects, it failed as a computer. Costs escalated from the $8 million estimate in 1966 to $31 million by 1972, despite construction of only a quarter of the planned multiprocessor. -
Nineteenth Status Report on Implementation
WORLD METEOROLOGICAL ORGANIZATION WORLD WEATHER WATCH NINETEENTH STATUS REPORT ON IMPLEMENTATION 1999 WMO-No. 894 Secretariat of the World Meteorological Organization - Geneva - Switzerland WORLD METEOROLOGICAL ORGANIZATION WORLD WEATHER WATCH NINETEENTH STATUS REPORT ON IMPLEMENTATION 1999 WMO-No.894 Secretariat of the World Meteorological Organization- Geneva- Switzerland © 1999, World Meteorological Organization ISBN 92- 63- 10894- 3 NOTE The designations employed and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the World Meteorological Organizati on concerning the legal status of any country, terri tory, city or area, of its authorities, or concern ing the delimitation of its frontiers or boundaries. FOREWORD The World Weather Watch (WWW) Programme of the World Meteorological Organization (WMO) was adopted in 1963 by the Fourth World Meteorological Congress. Since then it has grown to be fundamental for all WMO and other related programmes as regards the provision of basic meteorological data and products, telecommunication services and the management thereof. In continuing to attribute the highest priority to the furtherance and implementation of WWW, Twelfth Congress in Resolution 2 urged all Members of the Organization to cooperate actively and enthusiastically in the implementation of the WWW. This publication is the 19th in a series of biannual reports on the status of implementation of WWW. It was mainly designed to inform the senior management of the national Meteorological and Hydrological Services (NMHSs), but also interested academia and the private sector of the operational status of WWW. It provides information concerning the structure, status and trends of the implementation, as well as performance of the core components of WWW, notably the Global Observing System (GOS), the Global Telecommunication System (GTS) and the Global Data-processing System (GDPS). -
AVS on UNIX WORKSTATIONS INSTALLATION/ RELEASE NOTES
_________ ____ AVS on UNIX WORKSTATIONS INSTALLATION/ RELEASE NOTES ____________ Release 5.5 Final (50.86 / 50.88) November, 1999 Advanced Visual Systems Inc.________ Part Number: 330-0120-02 Rev L NOTICE This document, and the software and other products described or referenced in it, are con®dential and proprietary products of Advanced Visual Systems Inc. or its licensors. They are provided under, and are subject to, the terms and conditions of a written license agreement between Advanced Visual Systems and its customer, and may not be transferred, disclosed or otherwise provided to third parties, unless oth- erwise permitted by that agreement. NO REPRESENTATION OR OTHER AFFIRMATION OF FACT CONTAINED IN THIS DOCUMENT, INCLUDING WITHOUT LIMITATION STATEMENTS REGARDING CAPACITY, PERFORMANCE, OR SUI- TABILITY FOR USE OF SOFTWARE DESCRIBED HEREIN, SHALL BE DEEMED TO BE A WARRANTY BY ADVANCED VISUAL SYSTEMS FOR ANY PURPOSE OR GIVE RISE TO ANY LIABILITY OF ADVANCED VISUAL SYSTEMS WHATSOEVER. ADVANCED VISUAL SYSTEMS MAKES NO WAR- RANTY OF ANY KIND IN OR WITH REGARD TO THIS DOCUMENT, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PUR- POSE. ADVANCED VISUAL SYSTEMS SHALL NOT BE RESPONSIBLE FOR ANY ERRORS THAT MAY APPEAR IN THIS DOCUMENT AND SHALL NOT BE LIABLE FOR ANY DAMAGES, INCLUDING WITHOUT LIMI- TATION INCIDENTAL, INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES, ARISING OUT OF OR RELATED TO THIS DOCUMENT OR THE INFORMATION CONTAINED IN IT, EVEN IF ADVANCED VISUAL SYSTEMS HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. The speci®cations and other information contained in this document for some purposes may not be com- plete, current or correct, and are subject to change without notice. -
Hive: Fault Containment for Shared-Memory Multiprocessors
Hive: Fault Containment for Shared-Memory Multiprocessors John Chapin, Mendel Rosenblum, Scott Devine, Tirthankar Lahiri, Dan Teodosiu, and Anoop Gupta Computer Systems Laboratory Stanford University, Stanford CA 94305 htkp: //www-flash. skanforcl. edu Abstract In this paper we describe Hive, an operahng system designed for large-scale shared-memory multiprocessors. Hive is Reliability and scalability are major concerns when designing fundamentally different from previous monolithic and microkernel operating systems for large-scale shared-memory multiprocessors. SMP OS implementations: it IS structured as an internal distributed In this paper we describe Hive, an operating system with a novel system of independent kernels called ce/ls. This multicellular kernel architecture that addresses these issues Hive is structured kernel architecture has two main advantages: as an internal distributed system of independent kernels called ● Re[mbiltry: In SMP OS implementations, any significant cells. This improves reliabihty because a hardwme or software hardware or software fault causes the entire system to crash. fault damages only one cell rather than the whole system, and For large-scale machines this can result in an unacceptably low improves scalability because few kernel resources are shared by mean time to failure. In Hive, only the cell where the fault processes running on different cells. The Hive prototype is a occurred crashes, so only the processes using the resources of complete implementation of UNIX SVR4 and is targeted to run on that cell are affected. This is especially beneficial for compute the Stanford FLASH multiprocessor. server workloads where there are multiple independent This paper focuses on Hive’s solutlon to the following key processes. -
IRIX® Admin System Configuration and Operation
IRIX® Admin System Configuration and Operation 007-2859-017 COPYRIGHT © 1992-2001 Silicon Graphics, Inc. All rights reserved; provided portions may be copyright in third parties, as indicated elsewhere herein. No permission is granted to copy, distribute, or create derivative works from the contents of this electronic documentation in any manner, in whole or in part, without the prior written permission of Silicon Graphics, Inc. LIMITED RIGHTS LEGEND The electronic (software) version of this document was developed at private expense; if acquired under an agreement with the USA government or any contractor thereto, it is acquired as "commercial computer software" subject to the provisions of its applicable license agreement, as specified in (a) 48 CFR 12.212 of the FAR; or, if acquired for Department of Defense units, (b) 48 CFR 227-7202 of the DoD FAR Supplement; or sections succeeding thereto. Contractor/manufacturer is Silicon Graphics, Inc., 1600 Amphitheatre Pkwy 2E, Mountain View, CA 94043-1351. TRADEMARKS AND ATTRIBUTIONS Challenge, Indigo, IRIS, IRIX, Octane, and Onyx are registered trademarks and SGI, Crimson, Indigo2, IRIS FailSafe, IRIS InSight, IRIS WorkSpace, IRIX Networker, NUMAlink, Origin, Performance Co-Pilot, Power Challenge, Power Indigo2, Power Onyx, the SGI logo, and XFS are trademarks of Silicon Graphics, Inc. Indy is a registered trademark, used under license in the United States and owned by Silicon Graphics, Inc., in other countries worldwide. Centronics is a trademark of Centronics Data Computer Corporation. Cray is a registered trademark of Cray, Inc. Documenter’s Workbench is a trademark of Novell, Inc. FrameMaker, Illustrator, and PostScript are trademarks of Adobe Systems, Incorporated. -
Kingston Memory in Your System Contents
KINGSTON MEMORY IN YOUR SYSTEM CONTENTS page Introduction 2 1 System Specific Memory 2 1.1 Kingston Technology memory and your system’s warranty 2 1.1.1 Using Kingston Technology memory means your system warranty remains valid 2 1.1.2 Letter of confirmation from the Vice President, European Sales and Marketing 3 2 Kingston Technology Memory in Specific Manufacturers’ Systems 4 2.1 Kingston Technology memory in Compaq systems 4 2.1.1 Compaq recognition 5 2.1.2 Kingston Technology memory and Compaq’s Insight Manager® 5 2.2 Kingston Technology and Hewlett Packard 5 2.2.1 Hewlett Packard’s system warranty remains valid when using Kingston memory 5 2.2.2 Kingston’s partnership with Hewlett Packard 6 2.3 Kingston Technology and Sun Systems 6 2.3.1 Sun’s system warranty remains valid when using Kingston memory 6 2.3.2 Kingston Technology is a member of the Sun Developer Connection 6 2.3.2 Kingston Technology is part of the Cobalt Developer Network 6 3 Service Partnerships 7 3.1 Kingston Technology & SGI 7 3.1.1 Licensing Agreement 7 3.1.2 Kingston Technology’s European Service Agreement with SGI 7 4 Kingston Technology Strategic Relationships 8 4.1 Kingston Technology and Toshiba 8 4.2 Kingston Technology and Dell 9 4.3 Kingston Technology and Apple 9 4.4 Kingston Technology and JEDEC 9 4.5 Kingston Technology and Intel 9 4.6 Kingston Technology and Rambus 10 4.7 Kingston Technology and Microsoft 10 5 OEM Manufacturing 11 5.1 Some details of Kingston Technology’s OEM manufacturing 11 6 Why Kingston Technology Europe Ltd? 12 1 INTRODUCTION Kingston Technology is the world’s leading manufacturer of memory products, supplying more than 2000 products for over 4000 systems. -
Realtime Computer Graphics on Gpus Introduction
Real-time Algorithms Programmable Pipeline History Summary Realtime Computer Graphics on GPUs Introduction Jan Kolomazn´ık Department of Software and Computer Science Education Faculty of Mathematics and Physics Charles University in Prague March 3, 2021 1 / 55 Real-time Algorithms Programmable Pipeline History Summary Real-time Algorithms 2 / 55 Real-time Algorithms Programmable Pipeline History Summary REAL-TIME ALGORITHMS I Time Constrains: I Hard limit I Soft limit I CG examples: I Video frame rate I Cinema – 24 Hz I TV – 25 (50) Hz, 30 (60) Hz I Video games – 30–60 Hz I Virtual reality – frame rate doubled I Haptic rendering – 1 kHz 3 / 55 Real-time Algorithms Programmable Pipeline History Summary REAL-TIME ALGORITHMS I Time Constrains: I Hard limit I Soft limit I CG examples: I Video frame rate I Cinema – 24 Hz I TV – 25 (50) Hz, 30 (60) Hz I Video games – 30–60 Hz I Virtual reality – frame rate doubled I Haptic rendering – 1 kHz 4 / 55 Real-time Algorithms Programmable Pipeline History Summary REAL-TIME ALGORITHMS I Time Constrains: I Hard limit I Soft limit I CG examples: I Video frame rate I Cinema – 24 Hz I TV – 25 (50) Hz, 30 (60) Hz I Video games – 30–60 Hz I Virtual reality – frame rate doubled I Haptic rendering – 1 kHz 5 / 55 Real-time Algorithms Programmable Pipeline History Summary REAL-TIME ALGORITHMS I Time Constrains: I Hard limit I Soft limit I CG examples: I Video frame rate I Cinema – 24 Hz I TV – 25 (50) Hz, 30 (60) Hz I Video games – 30–60 Hz I Virtual reality – frame rate doubled I Haptic rendering – 1 kHz 6 / 55 Real-time Algorithms Programmable Pipeline History Summary REAL-TIME ALGORITHMS I Time Constrains: I Hard limit I Soft limit I CG examples: I Video frame rate I Cinema – 24 Hz I TV – 25 (50) Hz, 30 (60) Hz I Video games – 30–60 Hz I Virtual reality – frame rate doubled I Haptic rendering – 1 kHz 7 / 55 Real-time Algorithms Programmable Pipeline History Summary HOW TO ACHIEVE SPEED I Optimal algorithm (time complexity ?) I Approximations vs. -
Performance of Various Computers Using Standard Linear Equations Software
———————— CS - 89 - 85 ———————— Performance of Various Computers Using Standard Linear Equations Software Jack J. Dongarra* Electrical Engineering and Computer Science Department University of Tennessee Knoxville, TN 37996-1301 Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge, TN 37831 University of Manchester CS - 89 - 85 June 15, 2014 * Electronic mail address: [email protected]. An up-to-date version of this report can be found at http://www.netlib.org/benchmark/performance.ps This work was supported in part by the Applied Mathematical Sciences subprogram of the Office of Energy Research, U.S. Department of Energy, under Contract DE-AC05-96OR22464, and in part by the Science Alliance a state supported program at the University of Tennessee. 6/15/2014 2 Performance of Various Computers Using Standard Linear Equations Software Jack J. Dongarra Electrical Engineering and Computer Science Department University of Tennessee Knoxville, TN 37996-1301 Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge, TN 37831 University of Manchester June 15, 2014 Abstract This report compares the performance of different computer systems in solving dense systems of linear equations. The comparison involves approximately a hundred computers, ranging from the Earth Simulator to personal computers. 1. Introduction and Objectives The timing information presented here should in no way be used to judge the overall performance of a computer system. The results reflect only one problem area: solving dense systems of equations. This report provides performance information on a wide assortment of computers ranging from the home-used PC up to the most powerful supercomputers. The information has been collected over a period of time and will undergo change as new machines are added and as hardware and software systems improve. -
Lmbench: Portable Tools for Performance Analysis
The following paper was originally published in the Proceedings of the USENIX 1996 Annual Technical Conference San Diego, California, January 1996 lmbench: Portable Tools for Performance Analysis Larry McVoy, Silicon Graphics Carl Staelin, Hewlett-Packard Laboratories For more information about USENIX Association contact: 1. Phone: 510 528-8649 2. FAX: 510 548-5738 3. Email: [email protected] 4. WWW URL: http://www.usenix.org lmbench: Portable tools for performance analysis Larry McVoy Silicon Graphics, Inc. Carl Staelin Hewlett-Packard Laboratories Abstract of this benchmark suite obsolete or irrelevant. lmbench is a micro-benchmark suite designed to lmbench is already in widespread use at many focus attention on the basic building blocks of many sites by both end users and system designers. In some common system applications, such as databases, simu- cases, lmbench has provided the data necessary to lations, software development, and networking. In discover and correct critical performance problems almost all cases, the individual tests are the result of that might have gone unnoticed. lmbench uncovered analysis and isolation of a customer’s actual perfor- a problem in Sun’s memory management software that mance problem. These tools can be, and currently are, made all pages map to the same location in the cache, used to compare different system implementations effectively turning a 512 kilobyte (K) cache into a 4K from different vendors. In several cases, the bench- cache. marks have uncovered previously unknown bugs and lmbench measures only a system’s ability to design flaws. The results have shown a strong correla- transfer data between processor, cache, memory, net- tion between memory system performance and overall work, and disk. -
Performance of Various Computers Using Standard Linear Equations Software
———————— CS - 89 - 85 ———————— Performance of Various Computers Using Standard Linear Equations Software Jack J. Dongarra* Electrical Engineering and Computer Science Department University of Tennessee Knoxville, TN 37996-1301 Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge, TN 37831 University of Manchester CS - 89 - 85 September 30, 2009 * Electronic mail address: [email protected]. An up-to-date version of this report can be found at http://WWW.netlib.org/benchmark/performance.ps This Work Was supported in part by the Applied Mathematical Sciences subprogram of the Office of Energy Research, U.S. Department of Energy, under Contract DE-AC05-96OR22464, and in part by the Science Alliance a state supported program at the University of Tennessee. 9/30/2009 2 Performance of Various Computers Using Standard Linear Equations Software Jack J. Dongarra Electrical Engineering and Computer Science Department University of Tennessee Knoxville, TN 37996-1301 Computer Science and MatHematics Division Oak Ridge National Laboratory Oak Ridge, TN 37831 University of Manchester September 30, 2009 Abstract This report compares the performance of different computer systems in solving dense systems of linear equations. The comparison involves approximately a hundred computers, ranging from the Earth Simulator to personal computers. 1. Introduction and Objectives The timing information presented here should in no way be used to judge the overall performance of a computer system. The results reflect only one problem area: solving dense systems of equations. This report provides performance information on a wide assortment of computers ranging from the home-used PC up to the most powerful supercomputers. The information has been collected over a period of time and will undergo change as new machines are added and as hardware and software systems improve.