Course detail

Parallel and Distributed Algorithms

FIT-PRLAcad. year: 2021/2022

Introduction, features and languages for parallel and distributed architectures. Abstract models of parallel computing, PRAM, complexity. All prefix sums and their applications. Algorithms for parallel sorting and searching, parallel matrix operations, Interaction between processes, communication, synchronization. Typical problems.

Guarantor

doc. Dr. Ing. Petr Hanáček

Department

Department of Intelligent Systems (UITS)

Learning outcomes of the course unit

Students will learn basic principles of parallel and distributed computing and with parallel and distributed algorithms and their time complexity.
Students will learn basic principles and possibilities of algorithm parallelization.

Prerequisites

Basic knowledge of algorithms.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Literature

Reif, J: Synthesis of Parallel Algorithms, Morgan Kaufmann, 1993, ISBN:155860135X
Andrew Adamatzky, Selim Akl, Georgios Ch. Sirakoulis: From Parallel to Emergent Computing, CRC Press, 2019, ISBN 9781138054011
Akl, S.: The Design and Analysis of Parallel Algorithms, Prentice-Hall International, ISBN 0-13-200073-3
Ananth Grama, Anshul Gupta, George Karypis, Vipin Kumar: Introduction to Parallel Computing, Addison Wesley, 2003, ISBN: 0-201-64865-2
Jaja, J.: An Introduction to Parallel Algorithms, Addison-Wesley, 1992, ISBN 0-201-54856-9
Tvrdík, P.: Parallel Systems and Algorithms, skripta, Praha, Vydavatelství ČVUT 1997.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

A mid-term exam evaluation and an evaluation of projects.

Language of instruction

Czech

Work placements

Not applicable.

Aims

To acquaint students with the with the basic concepts of parallel and distributed computing. The course aims to the general principles of parallel and distributed algorithms and their time complexity.

Specification of controlled education, way of implementation and compensation for absences

A written mid-term test, a regular evaluation of projects. The test does not have correction option, the final exam has two possible correction terms.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MPV , any year of study, summer semester, 5 credits, compulsory-optional
    branch MGM , any year of study, summer semester, 5 credits, compulsory-optional
    branch MMM , any year of study, summer semester, 5 credits, compulsory
    branch MBI , 1. year of study, summer semester, 5 credits, compulsory
    branch MSK , 1. year of study, summer semester, 5 credits, compulsory
    branch MIS , 1. year of study, summer semester, 5 credits, compulsory
    branch MBS , 1. year of study, summer semester, 5 credits, compulsory
    branch MIN , 1. year of study, summer semester, 5 credits, compulsory

  • Programme MITAI Master's

    specialization NADE , 1. year of study, summer semester, 5 credits, compulsory
    specialization NBIO , 1. year of study, summer semester, 5 credits, compulsory
    specialization NGRI , 1. year of study, summer semester, 5 credits, compulsory
    specialization NNET , 1. year of study, summer semester, 5 credits, compulsory
    specialization NVIZ , 1. year of study, summer semester, 5 credits, compulsory
    specialization NCPS , 1. year of study, summer semester, 5 credits, compulsory
    specialization NSEC , 1. year of study, summer semester, 5 credits, compulsory
    specialization NEMB , 1. year of study, summer semester, 5 credits, compulsory
    specialization NHPC , 1. year of study, summer semester, 5 credits, compulsory
    specialization NISD , 1. year of study, summer semester, 5 credits, compulsory
    specialization NIDE , 1. year of study, summer semester, 5 credits, compulsory
    specialization NISY do 2020/21 , 1. year of study, summer semester, 5 credits, compulsory
    specialization NISY , 1. year of study, summer semester, 5 credits, compulsory
    specialization NMAL , 1. year of study, summer semester, 5 credits, compulsory
    specialization NMAT , 1. year of study, summer semester, 5 credits, compulsory
    specialization NSEN , 1. year of study, summer semester, 5 credits, compulsory
    specialization NVER , 1. year of study, summer semester, 5 credits, compulsory
    specialization NSPE , 1. year of study, summer semester, 5 credits, compulsory

Type of course unit

 

Lecture

39 hours, optionally

Teacher / Lecturer

doc. Dr. Ing. Petr Hanáček
doc. Ing. František Zbořil, Ph.D.

Syllabus

  • Introduction, architectures and languages for parallel and distributed processing.
  • Abstract models of parallel computing, PRAM (Parallel Random Access Machine).
  • Distributed and parallel algorithms and their complexity.
  • Interaction between processes, communication, synchronization.
  • Topologies, synchronous and asynchronous algorithms.
  • Algorithms for parallel sorting.
  • Algorithms for parallel searching.
  • Parallel matrix operations.
  • All prefix sums and their applications.
  • Graph and list algorithms.
  • Synchronization algorithms and tasks.
  • Mechanisms and language constructs for synchronization.
  • Languages for parallel and distributed computing.

Project

13 hours, compulsory

Teacher / Lecturer

Ing. František Vídeňský

Syllabus

  1. Programming project in parallel programming language.

eLearning

eLearning: currently opened course