Data Warehousing on the Cray CS6400: Oracle's Test-To-Scale Benchmark
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Distance Learning
Computing Service kekekeyyynotesnotesnotes Volume 25 Number 3 January 1999 Distance Learning Also in this Issue: Managed UNIX Workstations MIS News RALPHY 1 kkeeyynotesnotes Volume 25, Number 3 From the Editor Chris Joy explains the procedures by contents which the Computing Service is able to manage UNIX workstations on behalf of users, removing this burden news in brief from them. Turn to page 2 for more Windows 95 Login Problems 1 details. King's Manor Update 1 ❖❖❖ New National Service Computing Resources 1 On page 6, Gareth Johnson writes news about RALPHY, the Library's Managing UNIX Workstations 2 electronic reserve project, which is Distance Learning 3 providing students, on and off campus, with improved access to a mis range of publications. York Skills Management System 4 ❖❖❖ Postgraduate Degree Certificate Production 4 New Tuition Fees: New Software 5 Opposite, John Robinson details the Syllabus Plus 5 national computing services library available to academics within RALPHY 6 higher education. ❖❖❖ Finally, best wishes for the New Year. And keep an eye on the Millennium Countdown... Joanne Casey Information Officer millennium countdown 51 weeks to go! Are you prepared? See http:// www.york.ac.uk/services/cserv/offdocs/ y2k.htm for further information. 2 news brief in Windows 95 Login Problems Andrew Smith Since the start of last term, we have vicinity, could you please report it to (network, filestore, etc), it sometimes had a number of problems with users the Infodesk. It is a simple matter to takes a while to diagnose a fault not being able to login to an office or pick up the phone and leave a message report which may initially point to a classroom Windows 95 PC. -
Pthreads Primer
PThreads Primer A Guide to Multithreaded Programming Bil Lewis Daniel J. Berg SunSoft Press A Prentice Hall Title 1 1996 Sun Microsystems, Inc. — Printed in the United States of America. 2550 Garcia Avenue, Mountain View, California 94043-1100 U.S.A. All rights reserved. This book is protected by copyright and distributed under licenses restricting its use, copying, distribution, and decompilation. No part of this book may be reproduced in any form by any means without prior written authorization of Sun and its licensors, if any. Portions of the products described in this book may be derived from the UNIX® and Berkeley 4.3 BSD systems, licensed from UNIX System Laboratories, Inc., a wholly owned subsidiary of Novell, Inc., and the University of California, respectively. Third-party font software in this product is protected by copyright and licensed from Sun’s font suppliers. RESTRICTED RIGHTS LEGEND: Use, duplication, or disclosure by the United States government is subject to restrictions as set forth in DFARS 252.227-7013 (c)(1)(ii) and FAR 52.227-19. The products described in this book may be protected by one or more U.S. patents, foreign patents, or pending applications. TRADEMARKS— Sun, Sun Microsystems, the Sun logo, SunSoft, Solaris, Solaris Sunburst Design, OpenWindows, ONC, ONC+, SunOS, AnswerBook, Sun FORTRAN, Wabi, ToolTalk, NFS, XView, SunView, and The Network is the Computer are trademarks or registered trademarks of Sun Microsystems, Inc. UNIX is a registered trademark in the United States and other countries exclusively licensed through X/Open Company, Ltd. OPEN LOOK® is a registered trademark of Novell, Inc. -
Message Passing Dataflow Shared Memory
Introduction Introduction What is Parallel Architecture? Why Parallel Architecture? Evolution and Convergence of Parallel Architectures Fundamental Design Issues 2 What is Parallel Architecture? A parallel computer is a collection of processing elements that cooperate to solve large problems fast Some broad issues: • Resource Allocation: – how large a collection? – how powerful are the elements? – how much memory? • Data access, Communication and Synchronization – how do the elements cooperate and communicate? – how are data transmitted between processors? – what are the abstractions and primitives for cooperation? • Performance and Scalability – how does it all translate into performance? – how does it scale? 3 Why Study Parallel Architecture? Role of a computer architect: To design and engineer the various levels of a computer system to maximize performance and programmability within limits of technology and cost. Parallelism: • Provides alternative to faster clock for performance • Applies at all levels of system design • Is a fascinating perspective from which to view architecture • Is increasingly central in information processing 4 Why Study it Today? History: diverse and innovative organizational structures, often tied to novel programming models Rapidly maturing under strong technological constraints • The “killer micro” is ubiquitous • Laptops and supercomputers are fundamentally similar! • Technological trends cause diverse approaches to converge Technological trends make parallel computing inevitable • In the mainstream Need -
Resource Management
Resource Management Sun Microsystems, Inc. 901 San Antonio Road Palo Alto, CA 94303-4900 USA 650 960-1300 Fax 650 969-9131 Part No. 805-7268-10 July 1999, Revision A Send comments about this document to: [email protected] Copyright 1999 Sun Microsystems, Inc., 901 San Antonio Road • Palo Alto, CA 94303 USA. All rights reserved. This product or document is protected by copyright and distributed under licenses restricting its use, copying, distribution, and decompilation. No part of this product or document may be reproduced in any form by any means without prior written authorization of Sun and its licensors, if any. Third-party software, including font technology, is copyrighted and licensed from Sun suppliers. Parts of the product may be derived from Berkeley BSD systems, licensed from the University of California. UNIX is a registered trademark in the U.S. and other countries, exclusively licensed through X/Open Company, Ltd. Sun, Sun Microsystems, the Sun logo, AnswerBook, Java, the Java Coffee Cup, and Solaris are trademarks, registered trademarks, or service marks of Sun Microsystems, Inc. in the U.S. and other countries. All SPARC trademarks are used under license and are trademarks or registered trademarks of SPARC International, Inc. in the U.S. and other countries. Products bearing SPARC trademarks are based upon an architecture developed by Sun Microsystems, Inc. The OPEN LOOK and Sun™ Graphical User Interface was developed by Sun Microsystems, Inc. for its users and licensees. Sun acknowledges the pioneering efforts of Xerox in researching and developing the concept of visual or graphical user interfaces for the computer industry. -
No Slide Title
Cap 1 Introduction Introduction What is Parallel Architecture? Why Parallel Architecture? Evolution and Convergence of Parallel Architectures IC/Unicamp Fundamental Design Issues – Adaptado dos slides da editora por Mario Côrtes Mario por editorada slides dos Adaptado pag 1 2 What is Parallel Architecture? A parallel computer is a collection of processing elements that cooperate to solve large problems fast Some broad issues: • IC/Unicamp Resource Allocation: – – how large a collection? – how powerful are the elements? – how much memory? • Data access, Communication and Synchronization – how do the elements cooperate and communicate? – how are data transmitted between processors? – what are the abstractions and primitives for cooperation? • Performance and Scalability – how does it all translate into performance? – how does it scale? (satura o crescimento ou não) Adaptado dos slides da editora por Mario Côrtes Mario por editorada slides dos Adaptado 3 1.1 Why Study Parallel Architecture? Role of a computer architect: To design and engineer the various levels of a computer system to maximize performance and programmability within limits of technology cost IC/Unicamp and . – Parallelism: • Provides alternative to faster clock for performance (limitações de tecnologia) • Applies at all levels of system design (ênfase do livro: pipeline, cache, comunicação, sincronização) • Is a fascinating perspective from which to view architecture • Is increasingly central in information processing Côrtes Mario por editorada slides dos Adaptado pag 4 4 -
Efficiency of Shared-Memory Multiprocessors for a Genetic Sequence Similarity Search Algorithm
Technical Report Department of Computer Science University of Minnesota 4-192 EECS Building 200 Union Street SE Minneapolis, MN 55455-0159 USA TR 97-005 Efficiency of Shared-Memory Multiprocessors for a Genetic Sequence Similarity Search Algorithm by: Ed Huai-hsin Chi, Elizabeth Shoop, John Carlis, Ernest Retzel, and John Riedl Efficiency of Shared-Memory Multiprocessors for a Genetic Sequence Similarity Search Algorithm Ed Huai-hsin Chit, Elizabeth Shoop t, John Carlist, Ernest Retzelt, John Riedlt t Computer Science Department, t Computational Biology Centers. University of Minnesota Medical School. University of Minnesota 4-192 EE/CSci Building, Box 196. UMHC. 1460 Mayo Building, Minneapolis. MN 55455 420 Delaware Street S.E., [email protected] Minneapolis, MN 55455 January 3, 1997-Version #1 Abstract Molecular biologists who conduct large-scale genetic sequencing project5 are producing an ever-increa5ing amount of sequence data. GenBank, the primary repository for DNA sequence data, is doubling in size every 1.3 years. Keeping pace with the analysis of these data is a difficult task. One of the most successful technique, for analyzing genetic data is sequence similarity analysis-U1e comparison of unknown sequences against known ,equences kept in databases. As biologists gather more sequence data, sequence similarity algorithms are more and more useful, but take longer and longer to run. BLAST is one of the most popular sequence similarity algorithms in me today, but its running time is approximately proportional to the size of the database. Sequence similarity analysis using BLAST is becoming a bottleneck in genetic sequence analysis. This paper analyzes the performance of BLAST on SMPs, to improve our theoretical and practical understanding of the scalability of the algorithm. -
C I S a C Center for International Security and Arms Control
S t a n f o r d U n i v e r s i t y C I S A C Center for International Security and Arms Control The Center for International Security and Arms Control, part of Stanford University’s Institute for International Studies, is a multidisciplinary community dedicated to research and train- ing in the field of international security. The Center brings together scholars, policymakers, scientists, area specialists, members of the business community, and other experts to examine a wide range of international security issues. CISAC publishes its own series of working papers and reports on its work and also sponsors a series, Studies in International Se- curity and Arms Control, through Stanford University Press. Center for International Security and Arms Control Stanford University 320 Galvez Street Stanford, California 94305-6165 (415) 723-9625 http://www-leland.stanford.edu/group/CISAC/ Building on the Basics: An Examination of High-Performance Computing Export Control Policy in the 1990s Seymour Goodman, Peter Wolcott, Grey Burkhart A Report of the Center for International Security and Arms Control Stanford University November 1995 The Center for International Security and Arms Control, part of Stanford University's Institute for International Studies, brings together Stanford researchers from several scholarly disciplines with senior specialists from around the world and pre- and postdoctoral fellows for research projects, seminars and conferences, and international scholarly exchange. The Center publishes its own series of reports and papers on its work and also sponsors a series, Studies in International Security and Arms Control, through Stanford University Press. The Center is grateful to the Carnegie Corporation of New York for supporting this project. -
IEEE Signal Processing Magazine
Title Scalable Parallel Computers for Real-Time Signal Processing Author(s) Hwang, K; Xu, Z Citation IEEE - Signal Processing Magazine, 1996, v. 13 n. 4, p. 50-66 Issued Date 1996 URL http://hdl.handle.net/10722/44840 Rights Creative Commons: Attribution 3.0 Hong Kong License KAI HWANG and ZHlWEl XU n this article, we assess the state-of-the-art technology in to improve cost-effectiveness. We are most interested in massively parallel processors (MPPs) and their vari- scaling up by improving hardware and software resources to ations in different architectural platforms. Architectural expect proportional increase in performance. Scalability is a and programming issues are identified in using MPPs for multi-dimentional concept, ranging from resource, applica- time-critical applications such as adaptive radar signal proc- tion, to technology [ 12,27,37]. essing. Resource scalability refers to gaining higher performance First, we review the enabling technologies. These include or functionality by increasing the machine size (i.e., the high-performance CPU chips and system interconnects, dis- number of processors), investing in more storage (cache, tributed memory architectures, and various latency hiding main memory, disks), and improving the software. Commer- mechanisms. We characterize the concept of scalability in cial MPPs have limited resource scalability. For instance, the three areas: resources, applications, and technology. Scalable normal configuration of the IBM SP2 only allows for up to performance attributes are analytically defined. Then we com- 128 processors. The largest SP2 system installed to date is pare MPPs with symmetric multiprocessors (SMPs) and clus- the 5 12-node system at Come11 Theory Center [ 141, requiring ters of workstations (COWS). -
Linear Scalability on Decision Support Systems: Cray CS6400
Linear Scalability on Decision Support Systems: Cray CS6400 Brad Carlile, Cray Research, Inc., Business Systems Division 1 INTRODUCTION The nature of DSS systems is to iteratively refine and define new queries based on the information gathered from previous Decision Support Systems (DSS) manipulate and analyze queries. These queries are ad hoc and unpredictable. It is diffi- information to highlight previously un-explored relationships in cult to pre-plan for these types of queries since they are only large Gigabyte- or Terabyte- sized databases. They are executed once and a query may access millions or billions of emerging as an area of strategic value to many customers in the rows [1]. With ad hoc queries there is no perfect data layout, merchant RDBMS market who need to explore all of their data. especially when refreshing the database with inserts and updates In the past, lack of performance has prompted users to sample imbalances the original data layout. For predictable perfor- or to summarize data for DSS processing [1], however, mance on SMP systems, fine-grain distribution of data evenly sampling can hide valuable information. Insight can be gained across the disks provides equal access time to the data. Without by knowing the detail in the large database that summary data this equal time access of data, bottlenecks can degrade perfor- obliterates. Parallel processing enables completely scanning mance by orders of magnitude and serialize the processing. large database for this accurate detailed information in a reason- Such performance problems are a defining characteristic of able time. MPPs [6] [8]. Alternatively, high-performance SMP systems New powerful Solaris SMP systems, such as the are very flexible and capable. -
Parallel Computer Architectures
ΗΜΥ 656 ΠΡΟΧΩΡΗΜΕΝΗ ΑΡΧΙΤΕΚΤΟΝΙΚΗ ΗΛΕΚΤΡΟΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ Εαρινό Εξάμηνο 2007 ΔΙΑΛΕΞΗ 7: Parallel Computer Systems ΧΑΡΗΣ ΘΕΟΧΑΡΙΔΗΣ ([email protected]) Ack: Parallel Computer Architecture: A Hardware/Software Approach, David E. Culler et al, Morgan Kaufmann What is Parallel Architecture? • A parallel computer is a collection of processing elements that cooperate to solve large problems fast • Some broad issues: – Resource Allocation: • how large a collection? • how powerful are the elements? • how much memory? – Data access, Communication and Synchronization • how do the elements cooperate and communicate? • how are data transmitted between processors? • what are the abstractions and primitives for cooperation? – Performance and Scalability • how does it all translate into performance? • how does it scale? Why Study Parallel Architecture? • Role of a computer architect: – To design and engineer the various levels of a computer system to maximize performance and programmability within limits of technology and cost. • Parallelism: – Provides alternative to faster clock for performance – Applies at all levels of system design – Is a fascinating perspective from which to view architecture – Is increasingly central in information processing Why Study it Today? • History: diverse and innovative organizational structures, often tied to novel programming models • Rapidly maturing under strong technological constraints – The “killer micro” is ubiquitous – Laptops and supercomputers are fundamentally similar! – Technological trends cause diverse approaches to converge • Technological trends make parallel computing inevitable – In the mainstream • Need to understand fundamental principles and design tradeoffs, not just taxonomies – Naming, Ordering, Replication, Communication performance Inevitability of Parallel Computing • Application demands: Our insatiable need for cycles – Scientific computing: CFD, Biology, Chemistry, Physics, ... – General-purpose computing: Video, Graphics, CAD, Databases, TP.. -
World Weather Watch
WORLD METEOROLOGICAL ORGANIZATION WORLD WEATHER WATCH TWENTY-FIRST STATUS REPORT ON IMPLEMENTATION 2003 I WMO-No. 957 I Secretariat of the World Meteorological Organization - Geneva - Switzerland © 2003, World Meteorological Organization ISBN 92-63-10957-5 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 Organization concerning the legal status of any country, territory, city or area, of its authorities, or concerning the delimitation ofits frontiers or boundaries. CONTENTS Page FOREWORD............................................................................................................................................................ v FORTY YEARS OF WWW.................................................................................................................................... 1 EXECUTIVE SUMMARy............ 5 CHAPTER I- INTRODUCTION 7 Purpose and scope of the WWW Programme 7 Components of the WWW system..... 7 Organization ofWWW programmes '" 7 Relationship ofWWW with other programmes 8 CHAPTER 11- THE GLOBAL OBSERVING SYSTEM 9 Requirements for observational data.......................................................................................................................... 9 Implementation of the surface-based subsystem........................................................................................................ 9 Upper-air observations 10 Climatological observations...