Course detail

Parallel and Distributed Algorithms

FIT-PRLAcad. year: 2024/2025

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.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. František Zbořil, Ph.D.

Department

Department of Intelligent Systems (UITS)

Entry knowledge

Basic knowledge of algorithms.

Rules for evaluation and completion of the course

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

Prerequisites to obtain a credit
To obtain at least one point in each project and at least 15 points from semester activities.

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.
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.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

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
Reif, J: Synthesis of Parallel Algorithms, Morgan Kaufmann, 1993, ISBN:155860135X

Classification of course in study plans

  • Programme MITAI Master's

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

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

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

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 hod., compulsory

Teacher / Lecturer

Ing. Petr Veigend, Ph.D.

Syllabus

  1. Programming project in parallel programming language.