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Computer Engineering
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  • 6th Workshop on Self-Awareness in Cyber-Physical Systems (WORKSHOP WAS CANCELLED!)
    • Open Page "Teaching"
      • Open Page "Courses"
        • Open Page "SS 2025"
        • Eingebettete Systeme
        • Open Page "WS 2024/25"
        • Projektmanagement
        • Reconfigurable Computing
        • Systementwurf-Teamprojekt
        • Open Page "SS 2024"
        • Digitaltechnik
        • Eingebettete Systeme
    • Theses
      • Open Page "Project Groups"
      • WiFiSense
      • AutonomROS: Autonomous Car Swarm with Hardware-accelerated ROS Programming
      • CIRCA: An Approximate Computing Tool Flow
      • PG EML2
      • PG EML
      • High Performance Embedded Prosthetics Controller
      • PG ReCoTroy
      • Soundgates – Interactive Music Synthesis on FPGAs
      • Open Page "Sys­te­m­ent­wurfs-Team­pro­jekte"
      • FPGA-basiertes System zur Erkennung von Gebärdensprache
      • Approximate Computing: The design of intentionally incorrect digital hardware
      • Automatisierte Anwendungsanalyse für heterogene Rechnerknoten
    • Prak­ti­kum Mi­kro­con­trol­ler und In­ter­face-Elek­tro­nik
    • Teaching Statement
    • Open Page "Research"
    • Research Mission
    • Publications
    • Open Source Projekte
  1. Faculty of Computer Science, Electrical Engineering and Mathematics
  2. Institute of Computer Science
  3. Computer Engineering Group
  4. Research
  5. Research Mission

Re­search Mis­sion

Our research focus is on three innovative paradigms for building computing systems: reconfigurable computing, self-* computing, and approximate computing. The research mission is to study and investigate these paradigms, to develop novel architectures as well as design methods and tools for them, and to demonstrate their feasibility and usefulness by creating prototypical applications in the domains of embedded and high-performance computing.

Reconfigurable computing systems are built from reprogrammable hardware structures and can adapt their hardware architecture to the application under execution. This hardware-on-demand paradigm dramatically increases system flexibility and is beneficial for acceleration, for reducing energy consumption, and sometimes even for reducing cost.

Self-* computing systems can modify their behavior or structure without external control in reaction to changes in the system state or environment. Self-* capabilities are studied as a promising paradigm for future computing systems that will have to deal with unprecedented complexity, heterogeneity, and dynamics.

Approximate computing trades off computational accuracy against reductions in energy consumption, runtime, or hardware cost. This trade-off becomes possible since for many applications approximate, i.e., inaccurate, results are indeed good enough and often hard to distinguish from accurate results.

We also value research into novel technologies driven by demanding applications. In the past, we have worked on the classification of EMG signals for prosthesis control, on the use of advanced Monte-Carlo tree search methods for computer Go, and on the optimization of energy distribution networks. 

Over the last years our research has been supported by grants from the Deutsche Forschungsgemeinschaft (DFG), for example through the collaborative research center On-The-Fly Computing (CRC 901), the European Commission (EC), the German Federal Ministry for Education and Research (BMBF), the German Federal Ministry for Economic Affairs and Energy (BMWI), the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV), Microsoft, and Intel. 

Computer Engineering

Warburger Str. 100
33098 Paderborn
Germany

Universität Paderborn

Warburger Str. 100
33098 Paderborn
Germany

Phone University

+49 5251 60-0
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