Professorship for Operating Systems and Middleware

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At the group Operating Systems and Middleware led by Prof. Dr. Andreas Polze, work is done "close to the metal". Firstly, new hardware trends that are to be utilized. This involves programming paradigms, design patterns and description techniques for large, distributed component systems and data centers. Part of the focus is how to measure and control energy consumption there as well. The other metal involves rails: Several projects are exploring new architectures for flexible, distributed rail control systems to control signals and switches. We examine real-time capability, fault tolerance and reliability through simulated experiments, in our laboratory, and directly on the track.

current teaching activities

current projects

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SQuIRRL
Secure Quantum Infrastructure for Rail, Road, and Flight
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IoT Lab
A versatile facility for our research and teaching activities.
visualization of digital rail
Eisenbahninformatik
An academic research network for digital rail.

current open source projects

Metal FS
Near-storage compute-aware file system and FPGA operator pipelines.
simulate digital rail
Railway infrastructure model and toolchain for creation, modification, and export.
pgasus
A C++ parallel programming framework for NUMA systems, based on PGAS semantics.

For further projects, please refer to the OSM group on GitHub and the OSM group on GitLab.

current topics

The group's fields of research include but are not limited to the following topics.

resource management

  • dynamic workload management in distributed systems
  • dynamic, workload-dependent resource scaling (e.g., dynamic LPARs)
  • memory optimizations for virtual machines (e.g., memory migration benchmarks)
  • NUMA-aware programming with the PGASUS framework: applications, case studies, benchmarks
  • architectures of future server systems
  • lock-free data structures
  • multi-core/NUMA
  • advanced topology discovery with bandwidth and latency measurements: find shared interconnects

heterogeneous computing

  • high-level programming facilities for distributed GPU computing (e.g., CloudCL)
  • high-level programming facilities for FPGAs (e.g., CAPI SNAP, OpenCL)
  • virtualization / containerization for GPUs or FPGAs
  • FPGAs in IaaS cloud resources (e.g., Amazon F instances)
  • hardware-accelerated memory-compression (e.g., DEFLATE, 842 compression)
  • evaluation of integrated GPUs and APUs for latency-critical workloads (e.g., audio processing)
  • new programming languages & frameworks: CAPI SNAP, Radeon Open Compute, etc.

dependability

  • assessment and benchmarking
  • software fault injection (network, OS, communication, etc.)
  • fault tolerance through diversity
  • error detection – coverage vs. complexity
  • fault tolerance of service-oriented architectures
  • decentralized architectures
  • dependable operation
  • OS-provided fault tolerance
  • automation (lab, operation, assessment, etc.)

digital rail

  • cybersecurity for railway
  • security of railway protocols (e.g., GSM-R, ERTMS/ETCS, RaSTA, etc.)
  • interaction of safety and security
  • building safe and secure systems
  • digital planning documents, models, formats
  • digital Control Command and Signaling (CCS)
  • distributed, hybrid, co-simulated tests beds
  • interdisciplinary, cross-domain innovations
  • technology, concept transfer