Chemnitz University of Technology

Chemnitz University of Technology,
09107 Chemnitz, Germany
Prof. Gudula Rünger
Chemnitz University of Technology
Department of Computer Science,
Chair for Practical Computer Science,
09107 Chemnitz

Institution Background

Inventiveness and entrepreneurship – these characteristics of Chemnitz prepared the breeding ground for the tradition and scientific success of Chemnitz University of Technology since 1836. With more than 10.000 students and more than 1.700 staff members Chemnitz University of Technology today is a prospering, future-oriented and modern technical university with high scientific skills and great innovation potential. The profile of Chemnitz University of Technology, based on interdisciplinarity as well as on intensive networking on the national and international level, cross-links technical and natural sciences with social sciences, humanities and economics to generate competitive and excellent research as well as to create attractive degree programs.


Research Group Background

The department of computer science at Chemnitz University of Technology covers a broad range of computer science topics and offers a diverse bachelor and master program. In addition three specialization areas constitute the specific research and teaching profile. These areas are Parallel and Distributed Systems, Embedded Systems as well as Intelligent Multimedia Systems. A corresponding specialized master program in German and English attracts students from all over the world resulting in a high percentage of international students.

Prof. Gudula Rünger is the leader of the research area Parallel and Distributed Systems, which consists of research groups emphasizing on parallel algorithms, distributed and cloud computing, parallel hardware as well as parallel computing. Prof. Rünger specializes in tools, models and libraries for parallel programming, applications and scientific computing, performance model and prediction as well as energy efficiency.


Major Interest in Action Scientific Topics

  • Parallelization for ultrascale
  • Data management for large complex simulations
  • Energy efficiency in large scale systems
  • Applications amenable for ultrascale systems