Lecture Notes on Programming Concurrent Computer Systems

Total Page:16

File Type:pdf, Size:1020Kb

Lecture Notes on Programming Concurrent Computer Systems UNU/IIST International Institute for Software Technology Lecture Notes on Programming Concurrent Computer Systems Zhiming Liu May 2005 UNU/IIST Report No. 325 T UNU-IIST and UNU-IIST Reports UNU-IIST (United Nations University International Institute for Software Technology) is a Research and Training Centre of the United Nations University (UNU). It is based in Macau, and was founded in 1991. It started oper- ations in July 1992. UNU-IIST is jointly funded by the Governor of Macau and the governments of the People’s Republic of China and Portugal through a contribution to the UNU Endownment Fund. As well as providing two- thirds of the endownment fund, the Macau authorities also supply UNU-IIST with its office premises and furniture and subsidise fellow accommodation. The mission of UNU-IIST is to assist developing countries in the application and development of software tech- nology. UNU-IIST contributes through its programmatic activities: 1. Advanced development projects, in which software techniques supported by tools are applied, 2. Research projects, in which new techniques for software development are investigated, 3. Curriculum development projects, in which courses of software technology for universities in developing countries are developed, 4. University development projects, which complement the curriculum development projects by aiming to strengthen all aspects of computer science teaching in universities in developing countries, 5. Schools and Courses, which typically teach advanced software development techniques, 6. Events, in which conferences and workshops are organised or supported by UNU-IIST, and 7. Dissemination, in which UNU-IIST regularly distributes to developing countries information on interna- tional progress of software technology. Fellows, who are young scientists and engineers from developing countries, are invited to actively participate in all these projects. By doing the projects they are trained. At present, the technical focus of UNU-IIST is on formal methods for software development. UNU-IIST is an internationally recognised center in the area of formal methods. However, no software technique is universally applicable. We are prepared to choose complementary techniques for our projects, if necessary. UNU-IIST produces a report series. Reports are either Research R , Technical T , Compendia C or Adminis- trative A . They are records of UNU-IIST activities and research and development achievements. Many of the reports are also published in conference proceedings and journals. Please write to UNU-IIST at P.O. Box 3058, Macau or visit UNU-IIST’s home page: http://www.iist.unu.edu, if you would like to know more about UNU-IIST and its report series. G. M. Reed, Director UNU/IIST International Institute for Software Technology P.O. Box 3058 Macau Lecture Notes on Programming Concurrent Computer Systems Zhiming Liu Abstract Concurrent programming is the activity of constructing a program containing multiple processes that execute in parallel. The aim of the course is to introduce the basic concepts, principles and techniques in programming concurrent computing systems, and to provide practice in solving problems and skill in writing concurrent programs. The course will also provide methods for evaluating systems, algorithms and languages from a broad perspective. The course provides the students with understanding of the notations of concurrency, nondeterminism, synchronization, deadlock, livelock, safety and liveness. It provides students with the history of the development different language mechanisms for the realization of synchronization and interactions, in- cluding synchronization without using synchronization primitives, synchronization by semaphores, con- ditional regions, monitors, hand-shake communication and remote invocation. It covers communication via shared variables and message passing. We will take an informal but prices approach in the discussion of of requirements, design and valida- tion of concurrent programs. Zhiming Liu is a research fellow at UNU/IIST. His research interests include theory of computing sys- tems, including sound methods for specification, verification and refinement of fault-tolerant, real-time and concurrent systems, and formal techniques for OO development. His teaching interests are Com- munication and Concurrency, Concurrent and Distributed Programming, Software Engineering, Formal specification and Design of Computer Systems. E-mail: [email protected]. Copyright °c 2005 by UNU/IIST, Zhiming Liu Contents i Contents 1 PREFACE 1 1.1 Aims & Objectives . 1 1.2 Syllabus . 1 1.3 Reading List . 2 2 INTRODUCTION 3 2.1 Goals for Chapter 1 . 3 2.2 Course Organisation . 3 2.3 Reading List . 3 2.4 Course Assessment . 4 2.5 Overview . 4 2.6 Concurrent Programming . 5 2.6.1 Sequential programming . 5 2.6.2 Concurrent programming as partial ordering . 8 2.6.3 Concurrent programming as interleaving . 11 2.6.4 Concurrent computer systems . 13 2.7 The motivation for concurrent programming . 14 2.8 Problems in concurrent programming . 15 2.9 Seat Reservation Problem . 16 2.9.1 Critical sections and Mutual exclusion . 19 2.10 Concurrent programming in Pascal-FC . 20 2.11 Exercises . 24 3 MUTUAL EXCLUSION 27 3.1 Process interaction . 27 3.2 Active and passive entities . 28 3.3 Communication via shared variable . 28 3.3.1 The Ornamental Gardens problem . 29 3.4 Old-fashioned recipes for synchronization . 32 3.4.1 An old-fashioned recipe for condition synchronization . 33 3.4.2 Old-fashioned recipes for mutual exclusion . 34 3.5 Correctness of concurrent programs . 42 3.6 Exercises . 43 4 SEMAPHORES 51 4.1 Introducing Semaphores . 51 4.2 Definition of semaphores . 52 4.3 Mutual exclusion with semaphores . 54 4.4 Implementation of semaphores . 55 4.5 Analysing semaphore programs . 56 4.6 Condition synchronization with semaphores . 57 4.6.1 Producer and consumer with an unbounded buffer . 57 4.6.2 Producer-consumer with bounded buffers . 59 4.7 More examples . 62 Report No. 325, May 2005 UNU/IIST, P.O. Box 3058, Macau Contents ii 4.7.1 The Readers and Writers Problem . 62 4.7.2 The Dining Philosophers problem . 66 4.8 Final remarks on semaphores . 69 4.9 Exercises . 70 5 CONDITIONAL CRITICAL REGIONS AND MONITORS 72 5.1 Introduction . 72 5.2 Critical regions . 73 5.3 Conditional critical regions . 74 5.3.1 Example - condition synchronization . 76 5.4 Monitors . 78 5.4.1 The ideas behind monitors . 78 5.4.2 Definition of monitors . 79 5.4.3 Mutual exclusion with monitors . 80 5.4.4 Condition synchronization with monitors . 82 5.4.5 More examples . 85 5.4.6 Producer-Consumer with a bounded buffer . 85 5.4.7 Readers and writers . 87 5.4.8 Reasoning about monitor programs . 89 5.4.9 The expressiveness of monitors . 91 5.5 Exercises . 91 6 SYNCHRONOUS MESSAGE PASSINGS 93 6.1 Introduction . 93 6.2 Three forms of communication . 94 6.3 Naming the destinations and sources of messages . 95 6.4 Channels in Pascal-FC . 96 6.5 The types of channels . 96 6.6 A classification of distributed processes . 98 6.6.1 An network of filters – Prime number generation . 99 6.7 Synchronous channels . 102 6.8 Selective waiting construct . 103 6.9 Guarded alternatives . 106 6.10 The terminate alternative . 107 6.11 Else and timeout alternatives . 111 6.12 Exercises . 112 7 REMOTE INVOCATION 113 7.1 Introduction . 113 7.2 The message passing primitives in the remote invocation model . 114 7.3 Selective waiting with remote invocation . 119 7.4 Examples . 121 7.4.1 Resource allocation problem . 121 7.4.2 Dining philosophers problem . 123 7.4.3 Process idioms . 124 Report No. 325, May 2005 UNU/IIST, P.O. Box 3058, Macau Contents iii 7.4.4 A reactive example - a controlling system . 126 7.5 The limitation of the Pascal-FC select construct . 129 7.6 Exercises . 131 8 SUMMING UP 132 8.1 The course . ..
Recommended publications
  • 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.
    [Show full text]
  • Synchronization Spinlocks - Semaphores
    CS 4410 Operating Systems Synchronization Spinlocks - Semaphores Summer 2013 Cornell University 1 Today ● How can I synchronize the execution of multiple threads of the same process? ● Example ● Race condition ● Critical-Section Problem ● Spinlocks ● Semaphors ● Usage 2 Problem Context ● Multiple threads of the same process have: ● Private registers and stack memory ● Shared access to the remainder of the process “state” ● Preemptive CPU Scheduling: ● The execution of a thread is interrupted unexpectedly. ● Multiple cores executing multiple threads of the same process. 3 Share Counting ● Mr Skroutz wants to count his $1-bills. ● Initially, he uses one thread that increases a variable bills_counter for every $1-bill. ● Then he thought to accelerate the counting by using two threads and keeping the variable bills_counter shared. 4 Share Counting bills_counter = 0 ● Thread A ● Thread B while (machine_A_has_bills) while (machine_B_has_bills) bills_counter++ bills_counter++ print bills_counter ● What it might go wrong? 5 Share Counting ● Thread A ● Thread B r1 = bills_counter r2 = bills_counter r1 = r1 +1 r2 = r2 +1 bills_counter = r1 bills_counter = r2 ● If bills_counter = 42, what are its possible values after the execution of one A/B loop ? 6 Shared counters ● One possible result: everything works! ● Another possible result: lost update! ● Called a “race condition”. 7 Race conditions ● Def: a timing dependent error involving shared state ● It depends on how threads are scheduled. ● Hard to detect 8 Critical-Section Problem bills_counter = 0 ● Thread A ● Thread B while (my_machine_has_bills) while (my_machine_has_bills) – enter critical section – enter critical section bills_counter++ bills_counter++ – exit critical section – exit critical section print bills_counter 9 Critical-Section Problem ● The solution should ● enter section satisfy: ● critical section ● Mutual exclusion ● exit section ● Progress ● remainder section ● Bounded waiting 10 General Solution ● LOCK ● A process must acquire a lock to enter a critical section.
    [Show full text]
  • Edsger W. Dijkstra: a Commemoration
    Edsger W. Dijkstra: a Commemoration Krzysztof R. Apt1 and Tony Hoare2 (editors) 1 CWI, Amsterdam, The Netherlands and MIMUW, University of Warsaw, Poland 2 Department of Computer Science and Technology, University of Cambridge and Microsoft Research Ltd, Cambridge, UK Abstract This article is a multiauthored portrait of Edsger Wybe Dijkstra that consists of testimo- nials written by several friends, colleagues, and students of his. It provides unique insights into his personality, working style and habits, and his influence on other computer scientists, as a researcher, teacher, and mentor. Contents Preface 3 Tony Hoare 4 Donald Knuth 9 Christian Lengauer 11 K. Mani Chandy 13 Eric C.R. Hehner 15 Mark Scheevel 17 Krzysztof R. Apt 18 arXiv:2104.03392v1 [cs.GL] 7 Apr 2021 Niklaus Wirth 20 Lex Bijlsma 23 Manfred Broy 24 David Gries 26 Ted Herman 28 Alain J. Martin 29 J Strother Moore 31 Vladimir Lifschitz 33 Wim H. Hesselink 34 1 Hamilton Richards 36 Ken Calvert 38 David Naumann 40 David Turner 42 J.R. Rao 44 Jayadev Misra 47 Rajeev Joshi 50 Maarten van Emden 52 Two Tuesday Afternoon Clubs 54 2 Preface Edsger Dijkstra was perhaps the best known, and certainly the most discussed, computer scientist of the seventies and eighties. We both knew Dijkstra |though each of us in different ways| and we both were aware that his influence on computer science was not limited to his pioneering software projects and research articles. He interacted with his colleagues by way of numerous discussions, extensive letter correspondence, and hundreds of so-called EWD reports that he used to send to a select group of researchers.
    [Show full text]
  • Glossary of Technical and Scientific Terms (French / English
    Glossary of Technical and Scientific Terms (French / English) Version 11 (Alphabetical sorting) Jean-Luc JOULIN October 12, 2015 Foreword Aim of this handbook This glossary is made to help for translation of technical words english-french. This document is not made to be exhaustive but aim to understand and remember the translation of some words used in various technical domains. Words are sorted alphabetically. This glossary is distributed under the licence Creative Common (BY NC ND) and can be freely redistributed. For further informations about the licence Creative Com- mon (BY NC ND), browse the site: http://creativecommons.org If you are interested by updates of this glossary, send me an email to be on my diffusion list : • [email protected][email protected] Warning Translations given in this glossary are for information only and their use is under the responsability of the reader. If you see a mistake in this document, thank in advance to report it to me so i can correct it in further versions of this document. Notes Sorting of words Words are sorted by alphabetical order and are associated to their main category. Difference of terms Some words are different between the "British" and the "American" english. This glossary show the most used terms and are generally coming from the "British" english Words coming from the "American" english are indicated with the suffix : US . Difference of spelling There are some difference of spelling in accordance to the country, companies, universities, ... Words finishing by -ise, -isation and -yse can also be written with -ize, Jean-Luc JOULIN1 Glossary of Technical and Scientific Terms -ization and -yze.
    [Show full text]
  • The Deadlock Problem
    The deadlock problem More deadlocks mutex_t m1, m2; Same problem with condition variables void p1 (void *ignored) { • lock (m1); - Suppose resource 1 managed by c1, resource 2 by c2 lock (m2); - A has 1, waits on 2, B has 2, waits on 1 /* critical section */ c c unlock (m2); Or have combined mutex/condition variable unlock (m1); • } deadlock: - lock (a); lock (b); while (!ready) wait (b, c); void p2 (void *ignored) { unlock (b); unlock (a); lock (m2); - lock (a); lock (b); ready = true; signal (c); lock (m1); unlock (b); unlock (a); /* critical section */ unlock (m1); One lesson: Dangerous to hold locks when crossing unlock (m2); • } abstraction barriers! This program can cease to make progress – how? - I.e., lock (a) then call function that uses condition variable • Can you have deadlock w/o mutexes? • 1/15 2/15 Deadlocks w/o computers Deadlock conditions 1. Limited access (mutual exclusion): - Resource can only be shared with finite users. 2. No preemption: - once resource granted, cannot be taken away. Real issue is resources & how required • 3. Multiple independent requests (hold and wait): E.g., bridge only allows traffic in one direction - don’t ask all at once (wait for next resource while holding • - Each section of a bridge can be viewed as a resource. current one) - If a deadlock occurs, it can be resolved if one car backs up 4. Circularity in graph of requests (preempt resources and rollback). All of 1–4 necessary for deadlock to occur - Several cars may have to be backed up if a deadlock occurs. • Two approaches to dealing with deadlock: - Starvation is possible.
    [Show full text]
  • Fair K Mutual Exclusion Algorithm for Peer to Peer Systems ∗
    Fair K Mutual Exclusion Algorithm for Peer To Peer Systems ∗ Vijay Anand Reddy, Prateek Mittal, and Indranil Gupta University of Illinois, Urbana Champaign, USA {vkortho2, mittal2, indy}@uiuc.edu Abstract is when multiple clients are simultaneously downloading a large multimedia file, e.g., [3, 12]. Finally applications k-mutual exclusion is an important problem for resource- where a service has limited computational resources will intensive peer-to-peer applications ranging from aggrega- also benefit from a k mutual exclusion primitive, preventing tion to file downloads. In order to be practically useful, scenarios where all the nodes of the p2p system simultane- k-mutual exclusion algorithms not only need to be safe and ously overwhelm the server. live, but they also need to be fair across hosts. We pro- The k mutual exclusion problem involves a group of pro- pose a new solution to the k-mutual exclusion problem that cesses, each of which intermittently requires access to an provides a notion of time-based fairness. Specifically, our identical resource called the critical section (CS). A k mu- algorithm attempts to minimize the spread of access time tual exclusion algorithm must satisfy both safety and live- for the critical resource. While a client’s access time is ness. Safety means that at most k processes, 1 ≤ k ≤ n, the time between it requesting and accessing the resource, may be in the CS at any given time. Liveness means that the spread is defined as a system-wide metric that measures every request for critical section access is satisfied in finite some notion of the variance of access times across a homo- time.
    [Show full text]
  • Lecture 10: Fault Tolerance Fault Tolerant Concurrent Computing
    02/12/2014 Lecture 10: Fault Tolerance Fault Tolerant Concurrent Computing • The main principles of fault tolerant programming are: – Fault Detection - Knowing that a fault exists – Fault Recovery - having atomic instructions that can be rolled back in the event of a failure being detected. • System’s viewpoint it is quite possible that the fault is in the program that is attempting the recovery. • Attempting to recover from a non-existent fault can be as disastrous as a fault occurring. CA463 Lecture Notes (Martin Crane 2014) 26 1 02/12/2014 Fault Tolerant Concurrent Computing (cont’d) • Have seen replication used for tasks to allow a program to recover from a fault causing a task to abruptly terminate. • The same principle is also used at the system level to build fault tolerant systems. • Critical systems are replicated, and system action is based on a majority vote of the replicated sub systems. • This redundancy allows the system to successfully continue operating when several sub systems develop faults. CA463 Lecture Notes (Martin Crane 2014) 27 Types of Failures in Concurrent Systems • Initially dead processes ( benign fault ) – A subset of the processes never even start • Crash model ( benign fault ) – Process executes as per its local algorithm until a certain point where it stops indefinitely – Never restarts • Byzantine behaviour (malign fault ) – Algorithm may execute any possible local algorithm – May arbitrarily send/receive messages CA463 Lecture Notes (Martin Crane 2014) 28 2 02/12/2014 A Hierarchy of Failure Types • Dead process – This is a special case of crashed process – Case when the crashed process crashes before it starts executing • Crashed process – This is a special case of Byzantine process – Case when the Byzantine process crashes, and then keeps staying in that state for all future transitions CA463 Lecture Notes (Martin Crane 2014) 29 Types of Fault Tolerance Algorithms • Robust algorithms – Correct processes should continue behaving thus, despite failures.
    [Show full text]
  • Actor-Based Concurrency by Srinivas Panchapakesan
    Concurrency in Java and Actor- based concurrency using Scala By, Srinivas Panchapakesan Concurrency Concurrent computing is a form of computing in which programs are designed as collections of interacting computational processes that may be executed in parallel. Concurrent programs can be executed sequentially on a single processor by interleaving the execution steps of each computational process, or executed in parallel by assigning each computational process to one of a set of processors that may be close or distributed across a network. The main challenges in designing concurrent programs are ensuring the correct sequencing of the interactions or communications between different computational processes, and coordinating access to resources that are shared among processes. Advantages of Concurrency Almost every computer nowadays has several CPU's or several cores within one CPU. The ability to leverage theses multi-cores can be the key for a successful high-volume application. Increased application throughput - parallel execution of a concurrent program allows the number of tasks completed in certain time period to increase. High responsiveness for input/output-intensive applications mostly wait for input or output operations to complete. Concurrent programming allows the time that would be spent waiting to be used for another task. More appropriate program structure - some problems and problem domains are well-suited to representation as concurrent tasks or processes. Process vs Threads Process: A process runs independently and isolated of other processes. It cannot directly access shared data in other processes. The resources of the process are allocated to it via the operating system, e.g. memory and CPU time. Threads: Threads are so called lightweight processes which have their own call stack but an access shared data.
    [Show full text]
  • Mastering Concurrent Computing Through Sequential Thinking
    review articles DOI:10.1145/3363823 we do not have good tools to build ef- A 50-year history of concurrency. ficient, scalable, and reliable concur- rent systems. BY SERGIO RAJSBAUM AND MICHEL RAYNAL Concurrency was once a specialized discipline for experts, but today the chal- lenge is for the entire information tech- nology community because of two dis- ruptive phenomena: the development of Mastering networking communications, and the end of the ability to increase processors speed at an exponential rate. Increases in performance come through concur- Concurrent rency, as in multicore architectures. Concurrency is also critical to achieve fault-tolerant, distributed services, as in global databases, cloud computing, and Computing blockchain applications. Concurrent computing through sequen- tial thinking. Right from the start in the 1960s, the main way of dealing with con- through currency has been by reduction to se- quential reasoning. Transforming problems in the concurrent domain into simpler problems in the sequential Sequential domain, yields benefits for specifying, implementing, and verifying concur- rent programs. It is a two-sided strategy, together with a bridge connecting the Thinking two sides. First, a sequential specificationof an object (or service) that can be ac- key insights ˽ A main way of dealing with the enormous challenges of building concurrent systems is by reduction to sequential I must appeal to the patience of the wondering readers, thinking. Over more than 50 years, more sophisticated techniques have been suffering as I am from the sequential nature of human developed to build complex systems in communication. this way. 12 ˽ The strategy starts by designing —E.W.
    [Show full text]
  • 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.
    [Show full text]
  • Concurrent Computing
    Concurrent Computing CSCI 201 Principles of Software Development Jeffrey Miller, Ph.D. [email protected] Outline • Threads • Multi-Threaded Code • CPU Scheduling • Program USC CSCI 201L Thread Overview ▪ Looking at the Windows taskbar, you will notice more than one process running concurrently ▪ Looking at the Windows task manager, you’ll see a number of additional processes running ▪ But how many processes are actually running at any one time? • Multiple processors, multiple cores, and hyper-threading will determine the actual number of processes running • Threads USC CSCI 201L 3/22 Redundant Hardware Multiple Processors Single-Core CPU ALU Cache Registers Multiple Cores ALU 1 Registers 1 Cache Hyper-threading has firmware logic that appears to the OS ALU 2 to contain more than one core when in fact only one physical core exists Registers 2 4/22 Programs vs Processes vs Threads ▪ Programs › An executable file residing in memory, typically in secondary storage ▪ Processes › An executing instance of a program › Sometimes this is referred to as a Task ▪ Threads › Any section of code within a process that can execute at what appears to be simultaneously › Shares the same resources allotted to the process by the OS kernel USC CSCI 201L 5/22 Concurrent Programming ▪ Multi-Threaded Programming › Multiple sections of a process or multiple processes executing at what appears to be simultaneously in a single core › The purpose of multi-threaded programming is to add functionality to your program ▪ Parallel Programming › Multiple sections of
    [Show full text]
  • Download Distributed Systems Free Ebook
    DISTRIBUTED SYSTEMS DOWNLOAD FREE BOOK Maarten van Steen, Andrew S Tanenbaum | 596 pages | 01 Feb 2017 | Createspace Independent Publishing Platform | 9781543057386 | English | United States Distributed Systems - The Complete Guide The hope is that together, the system can maximize resources and information while preventing failures, as if one system fails, it won't affect the availability of the service. Banker's algorithm Dijkstra's algorithm DJP algorithm Prim's algorithm Dijkstra-Scholten algorithm Dekker's algorithm generalization Smoothsort Shunting-yard algorithm Distributed Systems marking algorithm Concurrent algorithms Distributed Systems algorithms Deadlock prevention algorithms Mutual exclusion algorithms Self-stabilizing Distributed Systems. Learn to code for free. For the first time computers would be able to send messages to other systems with a local IP address. The messages passed between machines contain forms of data that the systems want to share like databases, objects, and Distributed Systems. Also known as distributed computing and distributed databases, a distributed system is a collection of independent components located on different machines that share messages with each other in order to achieve common goals. To prevent infinite loops, running the code requires some amount of Ether. As mentioned in many places, one of which this great articleyou cannot have consistency and availability without partition tolerance. Because it works in batches jobs a problem arises where if your job fails — Distributed Systems need to restart the whole thing. While in a voting system an attacker need only add nodes to the network which is Distributed Systems, as free access to the network is a design targetin a CPU power based scheme an attacker faces a physical limitation: getting access to more and more powerful hardware.
    [Show full text]