DOCSLIB.ORG

Programming Languages for Distributed Computing Systems

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Programming Languages for Distributed Computing Systems HENRI E. BAL Department of Mathematics and Computer Science, Vrije Universiteit, Amsterdam, The Netherlands JENNIFER G. STEINER Centrum uoor Wiskunde en Znformatica, Amsterdam, The Netherlands ANDREW S. TANENBAUM Department of Mathematics and Computer Science, Vrije Uniuersiteit, Amsterdam, The Netherlands When distributed systems first appeared, they were programmed in traditional sequential languages, usually with the addition of a few library procedures for sending and receiving messages. As distributed applications became more commonplace and more sophisticated, this ad hoc approach became less satisfactory. Researchers all over the world began designing new programming languages specifically for implementing distributed applications. These languages and their history, their underlying principles, their design, and their use are the subject of this paper. We begin by giving our view of what a distributed system is, illustrating with examples to avoid confusion on this important and controversial point. We then describe the three main characteristics that distinguish distributed programming languages from traditional sequential languages, namely, how they deal with parallelism, communication, and partial failures. Finally, we discuss 15 representative distributed languages to give the flavor of each. These examples include languages based on message passing, rendezvous, remote procedure call, objects, and atomic transactions, as well as functional languages, logic languages, and distributed data structure languages. The paper concludes with a comprehensive bibliography listing over 200 papers on nearly 100 distributed programming languages. Categories and Subject Descriptors: C.2.4 [Computer-Communication Networks]: Distributed Systems-distributed applications; D.1.3 [Programming Techniques]: Concurrent Programming; D.3.3 [Programming Languages]: Language Constructs- concurrent programming structures; D.4.7 [Operating Systems]: Organization and Design-distributed systems General Terms: Languages, Design Additional Key Words and Phrases: Distributed data structures, distributed languages, distributed programming, functional programming, languages for distributed programming, languages for parallel programming, logic programming, object-oriented programming, parallel programming The research of H. E. Bal was supported in part by the Netherlands Organization for Scientific Research under Grant 125-30-10. J. G. Steiner’s current address: Open Software Foundation, Cambridge, MA. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. 0 1989 ACM 0360-0300/89/0900-0261$00.75 ACM Computing Surveys, Vol. 21, No. 3, September 1989 262 . H. E. Bal, J. G. Steiner, and A. S. Tanenbaum CONTENTS quired for implementing these applications. This programming support may be pro- vided either by the operating system or by a programming language. We briefly ex- INTRODUCTION amine the first option, and note several 1. DISTRIBUTED COMPUTING SYSTEMS disadvantages. 1.1 Classes of Distributed Applications In Section 2 we discuss the second op- 1.2 Requirements for Distributed Programming tion-special language support for pro- support 1.3 Languages for Distributed Programming gramming distributed computing systems. 2. LANGUAGE SUPPORT FOR PROGRAMMING We identify three issues that must be ad- DISTRIBUTED SYSTEMS dressed by a language intended to support 2.1 Parallelism distributed applications programming: the 2.2 Interprocess Communication and Synchronization ability to execute different pieces of a pro- 2.3 Partial Failure gram on different processors, the ability for 3. LANGUAGES FOR PROGRAMMING these pieces to cooperate with one another, DISTRIBUTED SYSTEMS and the ability to cope with (or take advan- 3.1 Languages with Logically Distributed tage of) partial failure of the distributed Address Spaces 3.2 Languages with Logically Shared system. We show how different languages Address Spaces have addressed these issues in very differ- 4. CONCLUSIONS ent ways, and how the appropriateness of APPENDIX one language over another depends primar- ACKNOWLEDGMENTS REFERENCES ily on the type of application to be written and, to a lesser extent, on the kind of dis- tributed system on which the application is to be implemented. INTRODUCTION In Section 3 we look at some represent- ative programming languages designed for During the past decade, many kinds of distributed computing systems. We divide distributed computing systems have been the languages into simple categories, de- proposed and built. These systems cover a scribing one or two examples from each wide spectrum in terms of design goals, category in some detail. We hope in this size, performance, and applications. They way to give a flavor of current research in also differ considerably in how they are this area. The languages we describe are programmed. Some are programmed in CSP, Occam, NIL, Ada,’ Concurrent C, conventional languages, possibly supple- Distributed Processes, SR, Emerald, mented with a few new library routines. Argus, Aeolus, ParAlfl, Concurrent PRO- Others are programmed in completely new LOG, PARLOG, Linda, and Orca. Finally, languages, specially designed for distrib- we present our conclusions and give an uted applications. It is the intention of this extensive bibliography. paper to describe and compare the methods and languages that can be used for pro- 1. DISTRIBUTED COMPUTING SYSTEMS gramming distributed systems, and to pres- ent in some detail several languages We begin this section with our definition representative of the research to date in of a distributed computing system. Noting this area. that there is a spectrum of such systems, There is no consensus in the literature characterized by their interconnecting net- as to the definition of a distributed com- work. We then discuss the kinds of appli- puting system, so we begin Section 1 by cations for which these systems are used. defining our use of this term. We then Next, we list the requirements for support- discuss the different kinds of distributed ing the programming of these applications. computing systems that have been built, the types of applications for which they are ’ Ada is a registered trademark of the U.S. Department intended, and the programming support re- of Defense. ACM Computing Surveys, Vol. 21, No. 3, September 1989 Programming Languages for Distributed Computing Systems l 263 Finally, we discuss how programming lan- but cooperate by sending messages over a guages can fulfill these requirements. communications network. There is considerable disagreement in the literature as to what constitutes a dis- Each processor in such a system executes tributed system. Among the many defini- its own instruction stream(s) and uses its tions that we have seen, there is only own local data, both stored in its local one point of agreement: They all require memory. Occasionally, processors may the presence of multiple processors. The need to exchange data; they do so by send- confusion may therefore be due to the large ing messagesto each other over a network. number of different architectural models Many different types of networks exist one finds in multiple-processor systems. (e.g., hypercube, local-area network, wide- Vector computers, for example, use many area networks), as will be discussed below. processors that simultaneously apply the Although these networks have very differ- same arithmetic operations to different ent physical properties, they all fit into the data [Russell 19781. They are best suited same model: each is a medium for trans- for computation-intensive numerical appli- ferring messages among processors (see cations. Dataflow and reduction machines Figure la). Distributed systems can be con- apply different operations to different data trasted with multiprocessors, in which pro- [Treleaven et al. 19821. Multiprocessors cessors communicate through a shared consist of several autonomous processors memory (see Figure lb). sharing a common primary memory [Jones Of the architectures mentioned in the and Schwarz 19801. These are well suited list of examples above, multicomputers, for running different subtasks of the same workstation-LANs, and workstation- program simultaneously. Multicomputers WANs qualify as distributed computing are similar to multiprocessors, except that systems by our definition. the processors do not share memory, but Distributed systems can be further char- rather communicate by sending messages acterized by their communications net- over a communications network [Athas and works. The network determines the speed Seitz 19881. As a final example, there are and reliability of interprocessor communi- systems comprised of workstations or min- cation, and the spatial distribution of the icomputers connected by a local- or wide- processors. Traditionally, a distributed ar- area network. This type of system is fre- chitecture in which communication is fast quently the target for distributed operating and reliable and where processors,are phys- systems [Tanenbaum and van Renesse ically close to one another is said to be 19851. (We will refer to these latter closely coupled; systems
Recommended publications
  • On-Line Computing with a Hierarchy of Processors

    On-Line Computing with a Hierarchy of Processors

    University of Pennsylvania ScholarlyCommons Technical Reports (CIS) Department of Computer & Information Science December 1968 On-Line Computing With a Hierarchy of Processors Richard P. Morton University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/cis_reports Recommended Citation Richard P. Morton, "On-Line Computing With a Hierarchy of Processors", . December 1968. University of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-69-13. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_reports/804 For more information, please contact [email protected]. On-Line Computing With a Hierarchy of Processors Abstract Time shared computer systems have been based upon the two techniques of multiprogramming and swapping. Multiprogramming is based on restricting each program to a portion of the total computer memory. Swapping requires considerable overhead time for loading and unloading programs. To alleviate the size restriction due to multiprogramming, segmentation is employed, resulting in fact in vastly increased swapping. A new system architecture is proposed for time shared computing that alleviates the high overhead or program size restriction. It utilizes a hierarchy of processors, where each processor is assigned tasks on the basis of four factors: interactive requirements, frequency of use, execution time, and program length. In order to study the hierarchical approach to system architecture, the Moore School Problem Solving Facility (MSPSF) was built and used. The study of the manner of operation and the reactions of the users clarified and defined the Hierarchy of Processors system architecture. The Moore School Problem Solving Facility was implemented on second generation equipment, the IBM 7040, and therefore it is not possible to adequately compare the efficiency with third generation computers operating in a swapping mode.
  • Distributed & Cloud Computing: Lecture 1

    Distributed & Cloud Computing: Lecture 1

    Distributed & cloud computing: Lecture 1 Chokchai “Box” Leangsuksun SWECO Endowed Professor, Computer Science Louisiana Tech University [email protected] CTO, PB Tech International Inc. [email protected] Class Info ■" Class Hours: noon-1:50 pm T-Th ! ■" Dr. Box’s & Contact Info: ●"www.latech.edu/~box ●"Phone 318-257-3291 ●"Email: [email protected] Class Info ■" Main Text: ! ●" 1) Distributed Systems: Concepts and Design By Coulouris, Dollimore, Kindberg and Blair Edition 5, © Addison-Wesley 2012 ●" 2) related publications & online literatures Class Info ■" Objective: ! ●"the theory, design and implementation of distributed systems ●"Discussion on abstractions, Concepts and current systems/applications ●"Best practice on Research on DS & cloud computing Course Contents ! •" The Characterization of distributed computing and cloud computing. •" System Models. •" Networking and inter-process communication. •" OS supports and Virtualization. •" RAS, Performance & Reliability Modeling. Security. !! Course Contents •" Introduction to Cloud Computing ! •" Various models and applications. •" Deployment models •" Service models (SaaS, PaaS, IaaS, Xaas) •" Public Cloud: Amazon AWS •" Private Cloud: openStack. •" Cost models ( between cloud vs host your own) ! •" ! !!! Course Contents case studies! ! •" Introduction to HPC! •" Multicore & openMP! •" Manycore, GPGPU & CUDA! •" Cloud-based EKG system! •" Distributed Object & Web Services (if time allows)! •" Distributed File system (if time allows)! •" Replication & Disaster Recovery Preparedness! !!!!!! Important Dates ! ■" Apr 10: Mid Term exam ■" Apr 22: term paper & presentation due ■" May 15: Final exam Evaluations ! ■" 20% Lab Exercises/Quizzes ■" 20% Programming Assignments ■" 10% term paper ■" 20% Midterm Exam ■" 30% Final Exam Intro to Distributed Computing •" Distributed System Definitions. •" Distributed Systems Examples: –" The Internet. –" Intranets. –" Mobile Computing –" Cloud Computing •" Resource Sharing. •" The World Wide Web. •" Distributed Systems Challenges. Based on Mostafa’s lecture 10 Distributed Systems 0.
  • Distributed Algorithms with Theoretic Scalability Analysis of Radial and Looped Load flows for Power Distribution Systems

    Distributed Algorithms with Theoretic Scalability Analysis of Radial and Looped Load flows for Power Distribution Systems

    Electric Power Systems Research 65 (2003) 169Á/177 www.elsevier.com/locate/epsr Distributed algorithms with theoretic scalability analysis of radial and looped load flows for power distribution systems Fangxing Li *, Robert P. Broadwater ECE Department Virginia Tech, Blacksburg, VA 24060, USA Received 15 April 2002; received in revised form 14 December 2002; accepted 16 December 2002 Abstract This paper presents distributed algorithms for both radial and looped load flows for unbalanced, multi-phase power distribution systems. The distributed algorithms are developed from tree-based sequential algorithms. Formulas of scalability for the distributed algorithms are presented. It is shown that computation time dominates communication time in the distributed computing model. This provides benefits to real-time load flow calculations, network reconfigurations, and optimization studies that rely on load flow calculations. Also, test results match the predictions of derived formulas. This shows the formulas can be used to predict the computation time when additional processors are involved. # 2003 Elsevier Science B.V. All rights reserved. Keywords: Distributed computing; Scalability analysis; Radial load flow; Looped load flow; Power distribution systems 1. Introduction Also, the method presented in Ref. [10] was tested in radial distribution systems with no more than 528 buses. Parallel and distributed computing has been applied More recent works [11Á/14] presented distributed to many scientific and engineering computations such as implementations for power flows or power flow based weather forecasting and nuclear simulations [1,2]. It also algorithms like optimizations and contingency analysis. has been applied to power system analysis calculations These works also targeted power transmission systems. [3Á/14].
  • Concurrent Programming Introduction

    Concurrent Programming Introduction

    v1.0 20130407 Programmazione Avanzata e Paradigmi Ingegneria e Scienze Informatiche - UNIBO a.a 2013/2014 Lecturer: Alessandro Ricci [module 2.1] CONCURRENT PROGRAMMING INTRODUCTION PAP LM - ISI - Cesena - UNIBO !1 SUMMARY • Concurrent programming – motivations: HW evolution – basic jargon • processes interaction, cooperation, competition, • mutual exclusion, synchronization • problems: deadlocks, starvation, livelocks • A little bit of history – Dijkstra, Hoare, Brinch-Hansen • Concurrent languages, mechanisms, abstractions – overview PAP LM - ISI - Cesena - UNIBO Introduction !2 CONCURRENCY AND CONCURRENT SYSTEMS • Concurrency as a main concept of many domains and systems – operating systems, multi-threaded and multi-process programs, distributed systems, control systems, real-time systems,... • General definitions – “In computer science, concurrency is a property of systems in which several computational processes are executing at the same time, and potentially interacting with each other.” [ROS-97] – “Concurrency is concerned with the fundamental aspects of systems of multiple, simultaneously active computing agents, that interact with one another” [CLE-96] • Common aspects – systems with multiple activities or processes whose execution overlaps in time – activities can have some kind of dependencies, therefore can interact PAP LM - ISI - Cesena - UNIBO Introduction !3 CONCURRENT PROGRAMMING • Concurrent programming – building programs in which multiple computational activities overlap in time and typically interact in some way • Concurrent program – finite set of sequential programs that can be executed in parallel, i.e. overlapped in time • a sequential program specifies sequential execution of a list of statements • the execution of a sequential program is called process • a concurrent program specifies two or more sequential programs that may be executed concurrently as parallel processes – the execution of a concurrent program is called concurrent computation or elaboration PAP LM - ISI - Cesena - UNIBO Introduction !4 CONCURRENT PROGRAMMING VS.
  • Data Definition Language

    Data Definition Language

    1 Structured Query Language SQL, or Structured Query Language is the most popular declarative language used to work with Relational Databases. Originally developed at IBM, it has been subsequently standard- ized by various standards bodies (ANSI, ISO), and extended by various corporations adding their own features (T-SQL, PL/SQL, etc.). There are two primary parts to SQL: The DDL and DML (& DCL). 2 DDL - Data Definition Language DDL is a standard subset of SQL that is used to define tables (database structure), and other metadata related things. The few basic commands include: CREATE DATABASE, CREATE TABLE, DROP TABLE, and ALTER TABLE. There are many other statements, but those are the ones most commonly used. 2.1 CREATE DATABASE Many database servers allow for the presence of many databases1. In order to create a database, a relatively standard command ‘CREATE DATABASE’ is used. The general format of the command is: CREATE DATABASE <database-name> ; The name can be pretty much anything; usually it shouldn’t have spaces (or those spaces have to be properly escaped). Some databases allow hyphens, and/or underscores in the name. The name is usually limited in size (some databases limit the name to 8 characters, others to 32—in other words, it depends on what database you use). 2.2 DROP DATABASE Just like there is a ‘create database’ there is also a ‘drop database’, which simply removes the database. Note that it doesn’t ask you for confirmation, and once you remove a database, it is gone forever2. DROP DATABASE <database-name> ; 2.3 CREATE TABLE Probably the most common DDL statement is ‘CREATE TABLE’.
  • Origins of Operating Systems OS/360 Martin Grund

    Origins of Operating Systems OS/360 Martin Grund

    Origins of Operating Systems OS/360 Martin Grund HPI Table of Contents ● IBM System 360 ● Functional Structure of OS/360 ● Virtual Machine Time Sharing Juni 2006 Origins of Operating Systems - OS/360 2 Martin Grund Welcome to Big Blue Juni 2006 Origins of Operating Systems - OS/360 3 Martin Grund IBM System 360 ● In 1964 IBM announced the IBM-360 family for computers ● All machines, despite their differences, had the same user instruction set ● Different operating systems available for these machines ● Only midrange and high-end system run OS/360 ● IBM introduced the new term of hardware architecture ● In 1970 IBM announced System 370 with hardware virtual memory support Juni 2006 Origins of Operating Systems - OS/360 4 Martin Grund IBM System 360 ● High-end machines established 32 bit as standard for computers ● Virtual Memory Support – hardware support for dynamic address translation ● Within ten years S/360 achieved standard status ● Flashback prices: ● 1970 – $279/MB hard disk ● 1980 - $35/MB hard disk | $50.000 /MB DRAM Juni 2006 Origins of Operating Systems - OS/360 5 Martin Grund IBM System 360 Specials ● Introduced 8bit entities ● Introduction of 32 or 64 bit floating point words based on a hexadecimal base ● Variable length strings using length field in the first byte ● All registers are universal registers – accumulators as well as address registers ● Registers use 32 bit, 24 bit for addressing -> 16MB Juni 2006 Origins of Operating Systems - OS/360 6 Martin Grund IBM S/360 - Pictures Juni 2006 Origins of Operating Systems -
  • Grid Computing: What Is It, and Why Do I Care?*

    Grid Computing: What Is It, and Why Do I Care?*

    Grid Computing: What Is It, and Why Do I Care?* Ken MacInnis <[email protected]> * Or, “Mi caja es su caja!” (c) Ken MacInnis 2004 1 Outline Introduction and Motivation Examples Architecture, Components, Tools Lessons Learned and The Future Questions? (c) Ken MacInnis 2004 2 What is “grid computing”? Many different definitions: Utility computing Cycles for sale Distributed computing distributed.net RC5, SETI@Home High-performance resource sharing Clusters, storage, visualization, networking “We will probably see the spread of ‘computer utilities’, which, like present electric and telephone utilities, will service individual homes and offices across the country.” Len Kleinrock (1969) The word “grid” doesn’t equal Grid Computing: Sun Grid Engine is a mere scheduler! (c) Ken MacInnis 2004 3 Better definitions: Common protocols allowing large problems to be solved in a distributed multi-resource multi-user environment. “A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.” Kesselman & Foster (1998) “…coordinated resource sharing and problem solving in dynamic, multi- institutional virtual organizations.” Kesselman, Foster, Tuecke (2000) (c) Ken MacInnis 2004 4 New Challenges for Computing Grid computing evolved out of a need to share resources Flexible, ever-changing “virtual organizations” High-energy physics, astronomy, more Differing site policies with common needs Disparate computing needs
  • IBM Application System/400 System/38-Compatible COBOL User's Guide and Reference

    IBM Application System/400 System/38-Compatible COBOL User's Guide and Reference

    IBM IBM Application System/400 SC09-1814-00 System/38-Compatible COBOL User’s Guide and Reference Note! Before using this information and the product it supports, be sure to read the general information under “Notices” on page xv. First Edition (June 1994) This edition applies to the System/38-Compatible feature of the IBM* ILE* COBOL/400* licensed program, (Program 5763-CB1), Version 3 Release 0 Modification 5, and to all subsequent releases and modifications until otherwise indi- cated in new editions. Make sure you are using the proper edition for the level of the product. Order publications through your IBM representative or the IBM branch serving your locality. Publications are not stocked at the address given below. A form for readers’ comments is provided at the back of this publication. If the form has been removed, you may address your comments to: IBM Canada Ltd. Laboratory Information Development 2G/345/1150/TOR 1150 Eglinton Avenue East, North York, Ontario, Canada M3C1H7 You can also send your comments by facsimile (attention: RCF Coordinator), or you can send your comments elec- tronically to IBM. See "Communicating your Comments to IBM" for a description of the methods. This page imme- diately precedes the Readers' Comment Form at the back of this publication. When you send information to IBM, you grant IBM a non-exclusive right to use or distribute the information in any way it believes appropriate without incurring any obligation to you. Copyright International Business Machines Corporation 1994. All rights reserved. Note to U.S. Government Users — Documentation related to restricted rights — Use, duplication or disclosure is subject to restrictions set forth in GSA ADP Schedule Contract with IBM Corp.
  • Preparation of Papers for AIAA Technical Conferences

    Preparation of Papers for AIAA Technical Conferences

    NASA KSC – Internship Final Report Unit Testing and Remote Display Development Nicholas Costa Kennedy Space Center Computer Science USRA Summer Session 18 07 2014 NASA Center 1 18/7/2014 NASA KSC – Internship Final Report Unit Testing and Remote Display Development Nicholas Costa Denison University, Granville, Ohio, Abstract The Kennedy Space Center is currently undergoing an extremely interesting transitional phase. The final Space Shuttle mission, STS-135, was completed in July of 2011. NASA is now approaching a new era of space exploration. The development of the Orion Multi- Purpose Crew Vehicle (MPCV) and the Space Launch System (SLS) launch vehicle that will launch the Orion are currently in progress. An important part of this transition involves replacing the Launch Processing System (LPS) which was previously used to process and launch Space Shuttles and their associated hardware. NASA is creating the Spaceport Command and Control System (SCCS) to replace the LPS. The SCCS will be much simpler to maintain and improve during the lifetime of the spaceflight program that it will support. The Launch Control System (LCS) is a portion of the SCCS that will be responsible for launching the rockets and spacecraft. The Integrated Launch Operations Applications (ILOA) group of SCCS is responsible for creating displays and scripts, both remote and local, that will be used to monitor and control hardware and systems needed to launch a spacecraft. It is crucial that the software contained within be thoroughly tested to ensure that it functions as intended. Unit tests must be written in Application Control Language (ACL), the scripting language used by LCS.
  • Computing at Massive Scale: Scalability and Dependability Challenges

    Computing at Massive Scale: Scalability and Dependability Challenges

    This is a repository copy of Computing at massive scale: Scalability and dependability challenges. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/105671/ Version: Accepted Version Proceedings Paper: Yang, R and Xu, J orcid.org/0000-0002-4598-167X (2016) Computing at massive scale: Scalability and dependability challenges. In: Proceedings - 2016 IEEE Symposium on Service-Oriented System Engineering, SOSE 2016. 2016 IEEE Symposium on Service-Oriented System Engineering (SOSE), 29 Mar - 02 Apr 2016, Oxford, United Kingdom. IEEE , pp. 386-397. ISBN 9781509022533 https://doi.org/10.1109/SOSE.2016.73 (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher’s website. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request.
  • The Programming Language Concurrent Pascal

    The Programming Language Concurrent Pascal

    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. SE-I, No.2, JUNE 1975 199 The Programming Language Concurrent Pascal PER BRINCH HANSEN Abstract-The paper describes a new programming language Disk buffer for structured programming of computer operating systems. It e.lt­ tends the sequential programming language Pascal with concurx:~t programming tools called processes and monitors. Section I eltplains these concepts informally by means of pictures illustrating a hier­ archical design of a simple spooling system. Section II uses the same enmple to introduce the language notation. The main contribu~on of Concurrent Pascal is to extend the monitor concept with an .ex­ Producer process Consumer process plicit hierarchy Of access' rights to shared data structures that can Fig. 1. Process communication. be stated in the program text and checked by a compiler. Index Terms-Abstract data types, access rights, classes, con­ current processes, concurrent programming languages, hierarchical operating systems, monitors, scheduling, structured multiprogram­ ming. Access rights Private data Sequential 1. THE PURPOSE OF CONCURRENT PASCAL program A. Background Fig. 2. Process. INCE 1972 I have been working on a new programming .. language for structured programming of computer S The next picture shows a process component in more operating systems. This language is called Concurrent detail (Fig. 2). Pascal. It extends the sequential programming language A process consists of a private data structure and a Pascal with concurrent programming tools called processes sequential program that can operate on the data. One and monitors [1J-[3]' process cannot operate on the private data of another This is an informal description of Concurrent Pascal.
  • Lecture 18: Parallel and Distributed Systems

    Lecture 18: Parallel and Distributed Systems

    Lecture 18: Parallel and What is a distributed system? Distributed Systems n From various textbooks: u “A distributed system is a collection of independent computers n Classification of parallel/distributed that appear to the users of the system as a single computer.” architectures u “A distributed system consists of a collection of autonomous n SMPs computers linked to a computer network and equipped with n Distributed systems distributed system software.” u n Clusters “A distributed system is a collection of processors that do not share memory or a clock.” u “Distributed systems is a term used to define a wide range of computer systems from a weakly-coupled system such as wide area networks, to very strongly coupled systems such as multiprocessor systems.” 1 2 What is a distributed system?(cont.) What is a distributed system?(cont.) n Michael Flynn (1966) P1 P2 P3 u n A distributed system is Network SISD — single instruction, single data u SIMD — single instruction, multiple data a set of physically separate u processors connected by MISD — multiple instruction, single data u MIMD — multiple instruction, multiple data one or more P4 P5 communication links n More recent (Stallings, 1993) n Is every system with >2 computers a distributed system?? u Email, ftp, telnet, world-wide-web u Network printer access, network file access, network file backup u We don’t usually consider these to be distributed systems… 3 4 MIMD Classification parallel and distributed Classification of the OS of MIMD computers Architectures tightly loosely coupled