Cluster Computing SS 2017

This is the homepage of the lecture Cluster Computing (Vorlesung) and its corresponding tutorial (Übung).


Cluster computers are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. This lecture provides an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented.

Organizational Matters

See the entry in the course catalog.


Target group

  • Computer Science Master students


  • Experience with computers and software as well as programing skills.


info KVV (course syllabus)

  • All participants need to have registered in the KVV (course syllabus)
    • Subscribe to »Cluster Computing S17«.


  • Lecture:
    • Tuesday, 10–12, room SR 140, Arnimallee 7
  • Tutorial:
    • Thursday, 12–14, room K 048, Takustr. 9

  • Exam:
    • 2017-07-20, 12:00–14:00, room SR 005, Takustr. 9

  • Post-Exam Review:
    • 2017-07-27, 13:00–14:00, room SR 006, Takustr. 9


  • The course language is German (or English if requested).
  • The exam will be formulated in German, but answers may be given in English, too.

Credits & Exams

The criteria for gaining credits are
  • active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
  • passing of the exam

Differences to privous lecture courses

  • 2017: neu lecture course



The actual slides are in English language.

  1. Organization:
  2. Introduction:
  3. Architecture:
  4. Performance Aspects:
    Performance Aspects
  5. Allocation Problems in Parallel Computers:
    Allocation Problems
  6. Basic Algorithms for Allocation Problems:
    Basic Algorithms
  7. The Quantitative Partitioning Problem:
    Quantitative Partitioning Problem
  8. Qualitative Partitioning:
    Qualitative Partitioning
  9. The Mapping Problem:
    Mapping Problem
  10. Load Balancing Problem:
    Load Balancing
  11. Scheduling of dependent threads:


Topic revision: r20 - 21 Jul 2017, GesineMilde
  • Printable version of this topic (p) Printable version of this topic (p)