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Concurrent Programming:  2012-2013

Lecturer

Degrees

Part A CoreComputer Science

Schedule B1Computer Science

Part AMathematics and Computer Science

Schedule B1(M&CS)Mathematics and Computer Science

Schedule AMSc in Advanced Computer Science

Term

Overview

Many challenges arise during the design and implementation of concurrent and distributed programs. The aim of this course is to understand those challenges, and to see techniques for tackling them. The main paradigm to be considered is message passing concurrency, where independent processes, with private variables, interact by passing messages.

Learning outcomes

At the end of the course students are expected to understand:
  • The conceptual foundations of concurrent programming, and
  • A variety of effective ways of structuring concurrent and distributed programs.

Prerequisites

This course combines well with the Concurrency course: Concurrent Programming helps provide motivation for Concurrency, while Concurrency helps to provide formal underpinnings for this course.  This course will assume some familiarity with CSP; students who are not taking the Concurrency course (or have not taken such a course previously) should read at least the first two chapters of that course's textbook.

Students should also have a basic understanding of Object Oriented Programming (objects, classes, interfaces, inheritance, abstract classes, polymorphism), e.g. as taught in the Michaelmas Term OOP course or the first year Imperative Programming 2 course.

The course will have a number of practicals, to allow students to gain experience with concurrent programming. These practicals will use Scala; background reading on the language will be suggested.

Synopsis

  • Introduction: reasons for concurrency; processes, threads; concurrent architectures; concurrent computing paradigms; safety and liveness; challenges of concurrent computing.
  • Message passing concurrency; deadlock; piplines; fine-grained concurrency.
  • Example: numerical integration using workers and a controller; bag of tasks.
  • Alternation: syntax, semantics, examples.
  • Client-server architectures.
  • Interacting peers: patterns of interaction: centralised, fully-connected, ring and tree topologies.
  • Synchronous data parallel computation.
  • Monitors: syntax and semantics; examples.
  • Patterns of concurrent computation: recursive parallel, bag of tasks with replacement, competition parallel, task parallel, map/reduce, revision of other patterns.
  • Semaphores: syntax and semantic; examples; passing the baton.

Syllabus

Reasons for concurrency; processes, threads; safety and liveness. Message passing concurrency; deadlock. Clients and servers. Interacting peers.  Synchronous parallel computation.  Patterns of concurrent programming: data parallel; bag of tasks; recursive parallel; task parallel.  Low-level concurrency controls: monitors; semaphores.

 

Reading list

 

  • Alternative: Principle of Concurrent and Distributed Programming, M. Ben-Ari, Prentice Hall, 1990.
  • Alternative background on Scala: Programming in Scala, Martin Odersky, Lex Spoon, Bill Venners, artima, 2008.
  • Taking our courses

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    Other matriculated University of Oxford students who are interested in taking this, or other, courses in the Department of Computer Science, must complete this online form by 17.00 on Friday of 0th week of term in which the course is taught. Late requests, and requests sent by email, will not be considered. All requests must be approved by the relevant Computer Science departmental committee and can only be submitted using this form.