Table of Contents

Lehrveranstaltung: High-Performance Data Analytics

Data-driven science requires the handling of large volumes of data in a quick period of time. Executing efficient workflows is challenging for users but also for systems. This module introduces concepts, principles, tools, system architectures, techniques, and algorithms toward large-scale data analytics using distributed and parallel computing. We will investigate the state-of-the-art of processing data of workloads using solutions in High-Performance Computing and Big Data Analytics.

Key information

Contact Julian Kunkel, Jonathan Decker
Location Virtual
Time Monday 16:15-17:45 (lecture), Monday 12:15-13:45 (lunch exercise, starts 1 week later)
Language English
Module Modul B.Inf.1712: Vertiefung Hochleistungsrechnen, Module M.Inf.1236: High-Performance Data Analytics
SWS 4
Credits 6
Contact time 56 hours
Independent study 124 hours
Exam Written date: 15.02.2024, 12-14 (Be punctual!), Geo MN14, 2nd exam: 28.03.2024 12-14, Geo MN14

Please note that we plan to record sessions (lectures and seminar talks) with the intent of providing the recordings via BBB to other students but also to publish and link the recordings on YouTube for future terms. If you appear in any of the recordings via voice, camera or screen share, we need your consent to publish the recordings. See also this Slide.

Topics

Topics cover:

Weekly laboratory practicals and tutorials will guide students to learn the concepts and tools. In the process of learning, students will form a learning community and integrate peer learning into the practicals. Students will have opportunities to present their solutions to the challenging tasks in the class. Students will develop presentation skills and gain confidence in the topics.

Learning Objectives

Examination

Written (90 Min.) or oral (ca. 30 Min.) → depends on the number of attendees.

See the learning objectives.

Agenda