Parallel (and Distributed) Algorithms (WS 2020/2021)


The lecture evaluation will take place on 01.12. from 10 to 12.

Lectures and tutorials will take place electronically.

  • Lectures will begin on 3.11. (Tuesday) at 10 ct.
  • Lectures and tutorials will be held live via screen sharing at the below mentioned times.
  • Access links to the streams will be made avaialble in Moodle (HRZ-account necessary).

Prof. Dr. Ulrich Meyer

Tue, 10:00 - 12:00
Thu, 10:00 - 12:00


Manuel Penschuck

Hung Tran

Please contact us via

Thu, 12.15 - 13.45


The lecture is held in English. By mutual agreement, the language of instruction can be changed to German, too.

You can solve the assignments in German or in English.


We shortly survey existing concepts of parallel computers (e.g., multicomputer clusters, shared-memory CPUs, and GPUs), and introduce theoretical abstractions of these machines. We start by analysing algorithms for multicomputers consisting of several independent compute nodes interconnected by a network. Based on the observation that practical algorithms for these machines typically seek to minimize communication costs, we discuss and quantify the impact of various network topologies. Subsequently, we develop and analyse distributed communication primitives and algorithms for classical problems, such as sorting.

We then switch to algorithms for multiprocessor architectures which are formally expressed by the PRAM model. This part emphasizes algorithms for linked lists and trees, search-, distribution-, and sorting problems and topics of graph theory. Throughout the lecture, we will analyze not only upper-bounds (leading to efficiency guarantees), but also consider lower-bounds: These include minimal costs for communication in certain topologies, the comparison of various PRAM variants, and the introduction of P-completeness to gain insight into the parallelizability of problems. Literature

  • A. Grama, A. Gupta, G. Karypis und V. Kumar: Introduction to Parallel Computing, second edition, Addison-Wesley 2003.
  • M. J. Quinn: Parallel Computing in C with MPI and OpenMP, McGraw-Hill, 2004.
  • J. JáJá: An Introduction to Parallel Algorithms, Addison-Wesley, 1992.
  • R.M. Karp und V. Ramachandran, Parallel algorithms for shared memory machines, in J van Leeuven (Ed.): Handbook of Theoretical Computer Science A, Kapitel 17, pp. 869-941, ElsevierScience Publishers, 1990.
  • P-completeness: R. Greenlaw, H.J. Hoover und W.L. Ruzzo: Limits to Parallel Computation, Oxford University Press, 1995.


Lecture notes

Some resources which might be useful



Assignment at 10 AMupdate 1 pm 10.11, removed exercise 1.3
Assignment at 10 AM-
Assignment 324.11.01.12 at 10 AM-