Publication list

Supervised Bachelor's theses of Karl Fuerlinger

1. Zhaoyuan Duan. Design und Evaluation of a Cluster-"top" Tool. 9 2025.
   BibTeX Entry

   @misc{duan25, author = {Zhaoyuan Duan}, title = {{Design} und {Evaluation} of a {Cluster-"top"} {Tool}}, year = {2025}, key = {duan25}, month = {9}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
2. Tim Kiebler. A new fast tool for strand-specific classification of HTS data sets: SeqStrandSpecificityChecker. 7 2025.
   BibTeX Entry

   @misc{kieb25, author = {Tim Kiebler}, title = {A new fast tool for strand-specific classification of {HTS} data sets: {SeqStrandSpecificityChecker}}, year = {2025}, key = {kieb25}, month = {7}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
3. Yihan Liu. Performance Analysis of Synchronization Mechanisms in Java. 9 2024.
   BibTeX Entry

   @misc{liu24, author = {Yihan Liu}, title = {{Performance} {Analysis} of {Synchronization} {Mechanisms} in {Java}}, year = {2024}, key = {liu24}, month = {9}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
4. Felix Rocke. Evaluation of C++ SIMD Libraries. 4 2023. PDF
   Abstract

   Single Instruction, Multiple Data (SIMD) units parallelize code through vectorization, thus enabling substantial performance improvements. Over the last two decades, SIMD units have become part of most CPUs. Despite this availability, many applications are not taking full advantage of SIMD units since utilizing the performance potential requires highly hardwaredependent instructions. However, the increase in performance and the substantial energy savings provided by these instructions should no longer be ignored, leading to the need for an e!cient SIMD API to allow for an e!cient and portable programming model. This thesis will evaluate six of the most popular SIMD libraries by reviewing their supported extensions, functions, documentation, and ease of use. Furthermore, we will benchmark the performance of the selected libraries using a floating point benchmark and compare their results to dedicated intrinsics implementations using the AVX2, AVX512, SVE, and NEON SIMD extensions. Finally, we will also take a closer look at Google’s SIMD library, Highway, which has been rising in popularity recently. We will assess if the library is ready to take on complex real-world algorithms by conducting a case study on the vectorization of an algorithm operating on unsigned integers. The results of the floating-point benchmark show that multiple libraries can match the performance of compiler intrinsics. Highway excelled with a strong performance across multiple SIMD extensions for the real-world integer algorithm. Thus, Highway may currently be the most suitable SIMD library for many software projects.
   BibTeX Entry

   @misc{rock23, author = {Felix Rocke}, title = {{Evaluation} of {C++} {SIMD} {Libraries}}, year = {2023}, pdf = {https://bib.nm.ifi.lmu.de/pdf/rock23.pdf}, abstract = {Single Instruction, Multiple Data (SIMD) units parallelize code through vectorization, thus enabling substantial performance improvements. Over the last two decades, SIMD units have become part of most CPUs. Despite this availability, many applications are not taking full advantage of SIMD units since utilizing the performance potential requires highly hardwaredependent instructions. However, the increase in performance and the substantial energy savings provided by these instructions should no longer be ignored, leading to the need for an e!cient SIMD API to allow for an e!cient and portable programming model. This thesis will evaluate six of the most popular SIMD libraries by reviewing their supported extensions, functions, documentation, and ease of use. Furthermore, we will benchmark the performance of the selected libraries using a floating point benchmark and compare their results to dedicated intrinsics implementations using the AVX2, AVX512, SVE, and NEON SIMD extensions. Finally, we will also take a closer look at Google’s SIMD library, Highway, which has been rising in popularity recently. We will assess if the library is ready to take on complex real-world algorithms by conducting a case study on the vectorization of an algorithm operating on unsigned integers. The results of the floating-point benchmark show that multiple libraries can match the performance of compiler intrinsics. Highway excelled with a strong performance across multiple SIMD extensions for the real-world integer algorithm. Thus, Highway may currently be the most suitable SIMD library for many software projects.}, key = {rock23}, month = {4}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger and Sergej Breiter}, type = {Bachelorthesis}, }
5. Jakub Orlowski. Hardware Topology Awareness Through a Graph Query API. 9 2021.
   BibTeX Entry

   @misc{orlo21, author = {Jakub Orlowski}, title = {{Hardware} {Topology} {Awareness} {Through} a {Graph} {Query} {API}}, year = {2021}, key = {orlo21}, month = {9}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger and Tobias Fuchs}, type = {Bachelorthesis}, }
6. Marcel Quanz. Automated Neural Network Parallelization Strategy Finding on a Supercomputer. 11 2020.
   BibTeX Entry

   @misc{quan20, author = {Marcel Quanz}, title = {{Automated} {Neural} {Network} {Parallelization} {Strategy} {Finding} on a {Supercomputer}}, year = {2020}, key = {quan20}, month = {11}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
7. Maximilian Lutz. Extension and Parallelisation of Voro++ for Moving-Mesh Hydrodynamical Simulations. 8 2020.
   BibTeX Entry

   @misc{lutz20a, author = {Maximilian Lutz}, title = {{Extension} and {Parallelisation} of {Voro++} for {Moving-Mesh} {Hydrodynamical} {Simulations}}, year = {2020}, key = {lutz20a}, month = {8}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
8. Nicco Mietzsch. Investigating the Parallel STL using the NAS Parallel Benchmark Suite. 11 2018.
   BibTeX Entry

   @misc{miet18, author = {Nicco Mietzsch}, title = {{Investigating} the {Parallel} {STL} using the {NAS} {Parallel} {Benchmark} {Suite}}, year = {2018}, key = {miet18}, month = {11}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
9. Benedikt Lehmann. DASH Performance and Usability Comparison to Chapel, Cilk, Go and TBB. 5 2018.
   BibTeX Entry

   @misc{lehm18, author = {Benedikt Lehmann}, title = {{DASH} {Performance} and {Usability} {Comparison} to {Chapel,} {Cilk,} {Go} and {TBB}}, year = {2018}, key = {lehm18}, month = {5}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
10. Daniel Diefenthaler. Online Visualization of Data Distribution Patterns. 5 2018.
    BibTeX Entry

    @misc{dief18, author = {Daniel Diefenthaler}, title = {{Online} {Visualization} of {Data} {Distribution} {Patterns}}, year = {2018}, key = {dief18}, month = {5}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
11. Tobias Kreuzholz. Evaluation von Hashtabellen zur Speicherung und Verarbeitung von Laufzeitereignissen in Parallelen Anwendungen. 2 2017.
    BibTeX Entry

    @misc{kreu17, author = {Tobias Kreuzholz}, title = {{Evaluation} von {Hashtabellen} zur {Speicherung} und {Verarbeitung} von {Laufzeitereignissen} in {Parallelen} {Anwendungen}}, year = {2017}, key = {kreu17}, month = {2}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger}, type = {Bachelorthesis}, }
12. Felix Mößbauer. DASH Benchmarking and Performance Assessment. 3 2016.
    BibTeX Entry

    @misc{moes16, author = {Felix Mößbauer}, title = {{DASH} {Benchmarking} and {Performance} {Assessment}}, year = {2016}, key = {moes16}, month = {3}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Karl Fuerlinger and Tobias Fuchs}, type = {Bachelorthesis}, }
13. Johannes Brechtmann. Visualisierung und Analyse von Speicherzugriffsmustern mit Valgrind. 11 2015.
    BibTeX Entry

    @misc{brec15, author = {Johannes Brechtmann}, title = {{Visualisierung} und {Analyse} von {Speicherzugriffsmustern} mit {Valgrind}}, year = {2015}, key = {brec15}, month = {11}, school = {Ludwig-Maximilians-Universität München}, supervisors = {Nils gentschen Felde and Karl Fuerlinger}, type = {Bachelorthesis}, }