Current Topics in Algorithms for Big Data (SS 2025)

Lecture

Prof. Dr. Ulrich Meyer

Tue 10:15 - 12:00 in SR 11

Wed 12:15 - 14:00 in SR 307

Office hours: By appointment

Tutorials

Alexander Leonhardt

Lukas Geis

Default is Wednesday 14:15 - 16:00 in SR 307, but upon mutual agreement we can try to find another slot.

Office hours: By appointment

Organisation of tutorials

We will issue problem sheets weekly on Tue; you have one week to complete the assignments and can hand them in before the next Tuesday 08:00 (a.m.) electronically. The solutions will then be discussed in the following tutorial. There are no (bonus) points for the exercises.

Language

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.

Content

In the first part we will consider classic and new algorithms for memory hierarchies

• For the external-memomy setting you can have a look at this book to be found in the CS library.

In the second part we will deal with streaming algorithms and their connection to other models of computation (external-memory, parallelism, power-aware computing). Lower bounds. Initial references:

• Lecture notes by Amit Chakrabarti at Dartmouth College from 2020. We will follow them rather closely for the first weeks of the second part.

• M. Garofalakis, J. Gehrke, and R. Rastogi (eds) “Data Stream Management: Processing High-Speed Data Streams”, Springer, 2016.

Exam

The exam type is to be determined.

Materials

• Vorlesungsmitschrift Effiziente Algorithmen 2015
• Folien zu Energie-effizientem Sortieren
• Ch. Scheideler “Probabilistic Methods for Coordination Problems”, HNI Verlagsschriftenreihe, 2000. Online PDF. Chapter 3 provides a nice little introduction to probability theory which will be handy for the course. Further notes on basic probability theory by Annamaria Kovacs can be found here.
• Some basics about hash functions by our former colleague Nicole Schweikardt. Please be aware of slightly different notation.

Lecture notes and extra material

Self Tests

tba

Assignments