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Module guide

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 field and terms:
  • Bachelor Computer Science 2019 (optional subject), major subject informatics, arbitrary semester
  • Bachelor Computer Science 2019 (optional subject), Canonical Specialization SSE, 4th semester
  • Bachelor Media Informatics 2020 (optional subject), computer science, 5th or 6th semester
  • Bachelor Robotics and Autonomous Systems 2020 (optional subject), computer science, 5th or 6th semester
  • Bachelor Computer Science 2016 (optional subject), Canonical Specialization Web and Data Science, 4th semester
  • Bachelor Computer Science 2016 (optional subject), major subject informatics, arbitrary semester
  • Bachelor Computer Science 2016 (optional subject), Canonical Specialization SSE, 4th semester
  • Bachelor Robotics and Autonomous Systems 2016 (optional subject), computer science, 5th or 6th semester
  • Bachelor IT-Security 2016 (optional subject), computer science, arbitrary semester
  • Master Medical Informatics 2014 (optional subject), computer science, 1st or 2nd semester
  • Bachelor Computer Science 2014 (optional subject), central topics of computer science, 5th or 6th semester
  • Master Computer Science 2012 (optional subject), advanced curriculum programming, 2nd and 3rd semester
  • Bachelor Computer Science 2012 (optional subject), central topics of computer science, 5th or 6th semester
  • Master Computer Science 2012 (optional subject), advanced curriculum algorithmics and complexity theory, 2nd or 3rd semester
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
Requires:
Responsible for this module:
Teachers:
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:

Prerequisites for attending the module:
- None

Prerequisites for the exam:
- Successful completion of homework assignments during the semester.

Letzte Änderung:
22.10.2019