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
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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
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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
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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.
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Grading through: |
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
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Language: |
Notes:Admission requirements for taking the module:
- None (the competencies of the modules listed under |
Letzte Änderung: 1.2.2022 |
für die Ukraine