Module CS3051-KP04, CS3051

Parallel Computing (ParallelVa)


Duration

1 Semester

Turnus of offer

normally each year in the summer semester

Credit points

4

Course of studies, specific fields and terms:

  • Bachelor Computer Science 2019, optional subject, major subject informatics
  • Bachelor Computer Science 2019, optional subject, Canonical Specialization SSE
  • Bachelor Media Informatics 2020, optional subject, computer science
  • Bachelor Robotics and Autonomous Systems 2020 , optional subject, computer science
  • Bachelor Computer Science 2016, optional subject, Canonical Specialization Web and Data Science
  • Bachelor Computer Science 2016, optional subject, major subject informatics
  • Bachelor Computer Science 2016, optional subject, Canonical Specialization SSE
  • Bachelor Robotics and Autonomous Systems 2016, optional subject, computer science
  • Bachelor IT-Security 2016, optional subject, computer science
  • Master Medical Informatics 2014, optional subject, computer science
  • Bachelor Computer Science 2014, optional subject, central topics of computer science
  • Master Computer Science 2012, optional subject, advanced curriculum programming
  • Bachelor Computer Science 2012, optional subject, central topics of computer science
  • Master Computer Science 2012, optional subject, advanced curriculum algorithmics and complexity theory

Classes and lectures:

  • Parallel Computing (exercise, 1 SWS)
  • Parallel Computing (lecture, 2 SWS)

Workload:

  • 45 hours in-classroom work
  • 65 hours private studies and exercises
  • 10 hours exam preparation

Contents of teaching:

  • Parallel architectures
  • Programming language support for parallel programming
  • Design methodologies for parallel algorithms
  • Implementation of parallel algorithms
  • Parallel search and sorting
  • Parallel graph algorithms
  • Parallel formula evaluation
  • Speedup, efficiency, parallel complexity classes
  • Limits of parallelism and lower bounds

Qualification-goals/Competencies:

  • Studentes are able to describe the design and function of parallel systems.
  • They are able to design and implement parallel algorithms.
  • They are able to analyze parallel systems and programs.
  • They are able to describe the limits of parallel systems.

Grading through:

  • Viva Voce or test

Responsible for this module:

Literature:

  • Jaja : An Introduction to Parallel Algorithms Addison Wesley, 1992
  • Quinn : Parallel Programming in C with MPI and OpenMP McGraw Hill, 2004

Language:

  • offered only in German

Notes:

Admission requirements for taking the module:
- None (the competencies of the modules listed under

Last Updated:

01.02.2022