Team Member: Dr. Karl Fuerlinger

Email	fuerling _at_ nm.ifi.lmu.de

Phone	+49 89 2180-9147
Fax	+49 89 2180-999146

Address	Dr. Karl Fuerlinger Ludwig-Maximilians-Universität München Institut für Informatik Oettingenstr. 67 D-80538 München Germany

Room	056

Research Interests

High-Performance Computing
Parallel and Distributed Computing
Heterogeneous Computing
Performance Analysis and Models
Numerical Linear Algebra Algorithms

Research Projects

Student work

Bachelor and Master theses

Students with an idea for a Bachelor or Master thesis roughly related to the above fields are always welcome to contact me. You may also take a look at the open proposals of the MNM-Team or at these open HPC-related thesis topics in collaboration with the LRZ.

Student Work

Work Completed:

Hilchenbach, S., CacheHound: Automated Reverse-Engineering of CPU Cache Policies in Modern Multiprocessors, Diplomarbeit, Ludwig-Maximilians-Universität München, September, 2024.
Liu, Y., Performance Analysis of Synchronization Mechanisms in Java, Bachelorarbeit, Ludwig-Maximilians-Universität München, September, 2024.
Quanz, M., Efficient Parallel Quantum Circuit Optimization using the ZX Calculus, Diplomarbeit, Ludwig-Maximilians-Universität München, Oktober, 2023.
Szostak, M., Application Fingerprinting using eBPF, Diplomarbeit, Ludwig-Maximilians-Universität München, August, 2023.
Rocke, F., Evaluation of C++ SIMD Libraries, Bachelorarbeit, Ludwig-Maximilians-Universität München, April, 2023.
Breiter, S., Evaluating Sector Caches in High-Performance Computing, Diplomarbeit, Ludwig-Maximilians-Universität München, Februar, 2022.
Uffmann, A., Entwicklung leistungsfähiger RMA-Locks durch Portierung und Optimierung von NUMA-Algorithmen, Diplomarbeit, Ludwig-Maximilians-Universität München, Februar, 2022.
Orlowski, J., Hardware Topology Awareness Through a Graph Query API, Bachelorarbeit, Ludwig-Maximilians-Universität München, September, 2021.
Diefenthaler, D., Hybrid Data Race Detection using CLR Profiling and IL Instrumentation, Diplomarbeit, Ludwig-Maximilians-Universität München, Juni, 2021.
Peralta Friedburg, S., Communication Offload Strategies for Multithreaded Distributed Memory Applications, 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.

Publications

Raoofy, A., Elis, B., Bode, V., Chung, M. T., Breiter, S., Schlemon, M., Herr, D.-F., Fuerlinger, K., Schulz, M., Weidendorfer, J., BEAST Lab: A Practical Course on Experimental Evaluation of Diverse Modern HPC Architectures and Accelerators , Journal of Computational Science Education, 2024(15), 23-31, März, 2024.
Breiter, S., Trotter, J. D., Fuerlinger, K., Modelling Data Locality of Sparse Matrix-Vector Multiplication on the A64FX, In Proceedings of the SC23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, 2023, 1334-1342, ACM, November, 2023.
Chung, M. T., Weidendorfer, J., Fuerlinger, K., Kranzlmüller, D., From Reactive to Proactive Load Balancing for Task-based Parallel Applications in Distributed Memory Machines, Journal of Concurrency and Computation: Practice and Experience (CCPE), e7828, Wiley, Juni, 2023.
Breiter, S., Weidendorfer, J., Chung, M. T., Fuerlinger, K., A Profiling-Based Approach to Cache Partitioning of Program Data, In Parallel and Distributed Computing, Applications and Technologies (PDCAT22), 453--463, Springer Nature Switzerland, April, 2023.
Chung, M. T., Weidendorfer, J., Fuerlinger, K., Kranzlmüller, D., Proactive Task Offloading for Load Balancing in Iterative Applications, In Parallel Processing and Applied Mathematics (PPAM 2022), 263-275, Springer, April, 2023.
Diep, D., Phuong, H. H., Fuerlinger, K., A general approach for supporting nonblocking data structures on distributed-memory systems, Journal of Parallel and Distributed Computing, vol. 173, pp. 48-60, Elsevier, März, 2023.
Zilk, F., Staudacher, K., Guggemos, T., Fuerlinger, K., Kranzlmüller, D., Walther, P., A compiler for universal photonic quantum computers, 2022, November, 2022.
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, (SC20), 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.

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