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Curriculum

Modul CS4170-KP06, CS4170SJ14

Parallel Computer Systems (ParaRSys14)

Duration:


1 Semester
Turnus of offer:


each winter semester
Credit points:


6
Course of studies, specific field and terms:
  • Certificate in Artificial Intelligence (compulsory), Artificial Intelligence, 1st semester
  • Master Entrepreneurship in Digital Technologies 2020 (advanced module), technology field computer science, Arbitrary semester
  • Master Computer Science 2019 (basic module), technical computer science, 1st or 2nd semester
  • Master Medical Informatics 2019 (optional subject), technical computer science, 1st or 2nd semester
  • Master Robotics and Autonomous Systems 2019 (optional subject), Elective, 1st or 2nd semester
  • Master IT-Security 2019 (basic module), technical computer science, 1st or 2nd semester
  • Master Medical Informatics 2014 (basic module), computer science, 1st or 2nd semester
  • Master Entrepreneurship in Digital Technologies 2014 (basic module), technology field computer science, 1st or 2nd semester
  • Master Computer Science 2014 (basic module), technical computer science, 1st or 2nd semester
Classes and lectures:
  • Parallel Computer Systems (exercise, 2 SWS)
  • Parallel Computer Systems (lecture, 2 SWS)
Workload:
  • 100 Hours private studies
  • 60 Hours in-classroom work
  • 20 Hours exam preparation
Contents of teaching:
  • Motivation and limitations for parallel processing
  • Parallel computing models
  • Taxonomy of parallel computers
  • Multi/manycore-systems
  • Graphic Processing Units (GPUs)
  • OpenCL
  • Specification languages
  • Hardware architectures
  • System management of many-core systems
Qualification-goals/Competencies:
  • Students are able to characterize different parallel computing architectures.
  • They are able to explain models of parallel computing.
  • They are able to make use of common programming interfaces for parallel computing systems.
  • They are able to judge which kind of parallel computing system is best suited for a dedicated problem and how many cores should be used.
  • They are able to evaluate the pros and cons of different hardware architectures.
  • They are able to write programs for parallel computing systems under considerations of the underlying hardware architecture.
  • They are able to compare methods for dynamic voltage and frequency scaling (DVFS) for manycore systems.
Grading through:
  • written exam
Responsible for this module:
Teachers:
Literature:
  • G. Bengel, C. Baun, M. Kunze, K. U. Stucky: Masterkurs Parallele und Verteilte Systeme - Vieweg + Teubner, 2008
  • M. Dubois, M. Annavaram, P. Stenström: Parallel Computer Organization and Design - University Press 2012
  • B. R. Gaster, L. Howes, D. R. Kaeli, P. Mistry, D. Schaa: Heterogeneous Computing with OpenCL - Elsevier/Morgan Kaufman 2013
  • B. Wilkinson; M. Allen: Parallel Programming - Englewood Cliffs: Pearson 2005
  • J. Jeffers, J. Reinders: Intel Xeon Phi Coprozessor High-Performance Programming - Elsevier/Morgan Kaufman 2013
  • D. A. Patterson, J. L. Hennessy: Computer Organization and Design - Morgan Kaufmann, 2013
Language:
  • offered only in German
Notes:

Admission requirements for taking the module:
- None

Admission requirements for participation in module examination(s):
- Successful completion of exercise assignments as specified at the beginning of the semester

Module Exam(s):
- CS4170-L1: Parallel Computer Systems, oral exam, 100% of the module grade

Letzte Änderung:
2.9.2021