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Team Member: Dr. Karl Fuerlinger

Email fuerling _at_
Phone +49 89 2180 9172
Fax +49 89 2180-9147
Address Dr. Karl Fuerlinger
Ludwig-Maximilians-Universität München
Institut für Informatik
Oettingenstr. 67
D-80538 München
Room E 005

Student Work

Work Completed:
  • Diefenthaler, D., Hybrid Data Race Detection using CLR Profiling and IL Instrumentation, Diplomarbeit, Ludwig-Maximilians-Universität München, Juni, 2021.
  • Quanz, M., Automated Neural Network Parallelization Strategy Finding on a Supercomputer, Bachelorarbeit, Ludwig-Maximilians-Universität München, November, 2020.
  • Lutz, M., Extension and Parallelisation of Voro++ for Moving-Mesh Hydrodynamical Simulations, Bachelorarbeit, Ludwig-Maximilians-Universität München, August, 2020.
  • Mietzsch, N., Investigating the Parallel STL using the NAS Parallel Benchmark Suite, Bachelorarbeit, Ludwig-Maximilians-Universität München, November, 2018.
  • Diefenthaler, D., Online Visualization of Data Distribution Patterns, Bachelorarbeit, Ludwig-Maximilians-Universität München, Mai, 2018.
  • Lehmann, B., DASH Performance and Usability Comparison to Chapel, Cilk, Go and TBB, Bachelorarbeit, Ludwig-Maximilians-Universität München, Mai, 2018.
  • Sellmair, M., Objektorientierte und Datenzentrische Parallelisierung einer Verkehrssimulation basierend auf dem Cell-Transmission-Model, Diplomarbeit, Ludwig-Maximilians-Universität München, März, 2018.
  • Jungblut, P., Untersuchung des Laufzeitverhaltens von C++ Containern, Diplomarbeit, Ludwig-Maximilians-Universität München, November, 2017.
  • Kreuzholz, T., Evaluation von Hashtabellen zur Speicherung und Verarbeitung von Laufzeitereignissen in Parallelen Anwendungen, Bachelorarbeit, Ludwig-Maximilians-Universität München, Februar, 2017.
  • Mößbauer, F., DASH Benchmarking and Performance Assessment, Bachelorarbeit, Ludwig-Maximilians-Universität München, März, 2016.
  • Saumweber, B., Supporting the PGAS Model on Modern Shared Memory Systems, Diplomarbeit, Ludwig-Maximilians-Universität München, Februar, 2016.
  • Brechtmann, J., Visualisierung und Analyse von Speicherzugriffsmustern mit Valgrind, Bachelorarbeit, Ludwig-Maximilians-Universität München, November, 2015.
  • Kowalewski, R., Nasty-MPI: A Systematic Stress Testing Approach for Correctness Debugging in MPI-3 RMA, Diplomarbeit, Ludwig-Maximilians-Universität München, November, 2015.
  • Zhou, L., Implementation of the Partitioned Global Address Space Model for Multi-GPU Systems, Diplomarbeit, Ludwig-Maximilians-Universität München, November, 2014.
  • Fuchs, T., Evaluation of Task Scheduling Algorithms and Wait-Free Data Structures for Embedded Multi-Core Systems, Diplomarbeit, Ludwig-Maximilians-Universität München, Oktober, 2014.
  • Bleimhofer, B., Hierarchical Arrays for Efficient and Productive Data-Intensive Parallel Computing, Diplomarbeit, Ludwig-Maximilians-Universität München, August, 2012.


  • Diep, D., Fuerlinger, K., Nonblocking Data Structures for Distributed-Memory Machines: Stacks as an Example, In 2021 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pp. 9-17, IEEE, Valladolid, Spain, März, 2021.
  • Chung, M. T., Weidendorfer, J., Samfass, P., Fuerlinger, K., Kranzlmüller, D., Scheduling across Multiple Applications using Task-Based Programming Models, In 2020 IEEE/ACM Fourth Annual Workshop on Emerging Parallel and Distributed Runtime Systems and Middleware (IPDRM), In conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, (SC 20), November, 2020.
  • Diep, D., Kien, T. P., Fuerlinger, K., Nam, T., A time-stamping system to detect memory consistency errors in MPI one-sided applications, Parallel Computing, vol. 86, pp. 36-44, Elsevier, August, 2019.
  • Diep, D., Fuerlinger, K., Nam, T., MC-CChecker: A Clock-Based Approach to Detect Memory Consistency Errors in MPI One-Sided Applications, In 25th European MPI Users Group Meeting (EuroMPI), pp. 9:1-9:11, ACM, Barcelona, Spain, September, 2018.
  • Fuchs, T., Fuerlinger, K., A Multidimensional Distributed Array Abstraction for PGAS, In Proceedings of the 18th {IEEE} International Conference on High Performance Computing and Communications (HPCC 2016), 2016, 1061-1068, IEEE CS CPS, Sydney, Australia, Dezember, 2016.
  • Fuchs, T., Fuerlinger, K., Expressing and Exploiting Multidimensional Locality in DASH, In Software for Exascale Computing - SPPEXA 2013-2015, 2016, 341-359, Springer, Garching, Germany, Januar, 2016.
  • Fuerlinger, K., Glass, C., Gracia, J., Knüpfer, A., Tao, J., Hünich, D., Idrees, K., Maiterth, M., Mbedheb, Y., Zhou, H., DASH: Data Structures and Algorithms with Support for Hierarchical Locality, In Euro-Par 2014 Workshops , Porto, Portugal, August, 2014.
  • Fuerlinger, K., Klausecker, C., Kranzlmüller, D., Towards Energy Efficient Parallel Computing on Consumer Electronic Devices, In ICT-GLOW 2011, Toulouse, France, September, 2011.
  • Fuerlinger, K., Wright, N. J., Skinner, D., Klausecker, C., Kranzlmüller, D., Effective Holistic Performance Measurement at Petascale Using IPM, In Proceedings of CiHPC: Competence in High Performance Computing, Schwetzingen, Germany, Mai, 2010.