Application

We offer Bachelor theses, Master theses, and student practicals in the research areas of the HAWAII Lab.

While not mandatory, we generally recommend completing a practical before starting a thesis. This gives students more time to become familiar with the research topic, tools, and workflow, and in our experience often leads to more successful thesis projects.

Applications should be sent to hawaii-thesis@uni-heidelberg.de.

What to include

To help us evaluate your background and identify suitable thesis topics, please include:

  • A short CV
  • A transcript of records (or another overview of your academic background). We are primarily interested in the courses you have completed, particularly those related to our research areas, as many thesis topics require knowledge from one or more of our lectures.
  • A brief motivation statement describing your research interests and the types of projects you would like to work on.

When to apply

We encourage students to apply well in advance of their intended start date. Finding a suitable topic and supervisor requires internal discussion, which typically takes several weeks. Contacting us early therefore increases the chances of finding a project that is a good match for both your interests and our current research activities.

Finding a topic

A good starting point for learning about our research are our lecture (see the Teaching page for an overview). You may also browse our Research Projects, our recent Publications and previously completed Theses to get an overview of the topics we work on.

We are happy to consider thesis topic proposals from students. However, our standard procedure is to match applicants against our internal list of available thesis topics based on their academic background, interests, and the prerequisites required for each project.

Completed Bachelor and Master Theses

Bachelor

  1. Marco Lorenz, Characterizing Detection Transformers for Hands, Guns and Phones with Roofline Methodology, Bachelor Computer Science, Heidelberg University, supervised by Holger Fröning and E. W. Bethel, 2024
  2. Jonathan Bernhard, Optimized bit-serial operations on 64-bit ARM processors using TVM compilation and LIKWID profiling, Bachelor Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2023
  3. Constantin Nicolai, High resolution energy measurements of embedded ML workloads, Bachelor Physics, Department of Physics and Astronomy, Heidelberg University, supervised by Holger Fröning and Johannes Schemmel, 2022
  4. Florian Nowak, Instantiating the energy-based roofline model using hardware performance counters, Bachelor Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Felix Zahn, 2021
  5. Raphael Kirchholtes, Data management for easy analysis of HPC communication traces, Bachelor Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2020
  6. Otto von Zastrow-Marcks, Knowledge distillation for faster image segmentation, Bachelor Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2020
  7. Georg Weisert, CUDA Unified Memory - A deep dive, Bachelor Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2020
  8. Lisa Kuhn, Quantized neural networks for keyword spotting on neuromorphic hardware, Bachelor Computational Linguistics, Institute of Computational Linguistics, Heidelberg University, supervised by Stefan Riezler and Holger Fröning, 2020
  9. Matthias Hauck, A management environment for MEMSCALE, Bachelor Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2012

Master

  1. Congcong Xu, Bayesian Bridge: Transferring Posterior Predictions between Models Trained via Markov Chain Monte Carlo and Stochastic Variational Inference, Master Scientific Computing, Heidelberg University, supervised by Holger Fröning and Gregor Schiele, 2024
  2. Prakiti Jain, Image Corruption on Object Detection Data to Evaluate Uncertainty Estimation, Master Data and Computer Science, Heidelberg University, supervised by Holger Fröning and Ullrich Köthe, 2024
  3. Xiao Wang, Evaluating Robustness Methods for DNNs under Noisy Computations, Master Scientific Computing, Heidelberg University, supervised by Holger Fröning and Artur Andrzejak, 2024
  4. Yi Zhang, Utilizing Machine Learning Methods for Time Series Classification, Master Scientific Computing, Heidelberg University, supervised by Holger Fröning and Yufei Mao, 2024
  5. Hadi Ghaeni, Analysis of the Suitability of Federated Learning Approaches for Quality Data of Eroding Products, Master Computer Engineering, Heidelberg University, supervised by Holger Fröning and Benjamin Kormann, 2024
  6. Lisa Kuhn, Scalability of Bayesian neural network inference methods for real-world tasks, Master Data and Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Franz Pernkopf, 2023
  7. Christian Alles, On the performance of butterfly approximations on the GraphCore IPU, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Kazem Shekofteh, 2023
  8. Daniel Barley, Reducing the state of large-scale MLPs by compressing the backward pass, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Stefan Riezler, 2023
  9. Eric Matthias Kern, Optimized calibration for analog computations targeting deep neural networks on the example of BrainScaleS-2, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Johannes Schemmel, 2023
  10. Falk Selker, Optimization of an approximation based approach to Bayesian neural networks with TVM on embedded hardware, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Franz Pernkopf, 2023
  11. Tobias Richstein, Characterization and approximation of the backwards path of large-scale language models, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Stefan Riezler, 2022
  12. Torben Krieger, Towards hardware-aware automatic compression of neural networks, Master Data and Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Ullrich Köthe, 2022
  13. Florian Brunner, Designing hardware-efficient convolutional neural networks via reinforcement learning based neural architecture search, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Ullrich Köthe, 2021
  14. Hendrik Borras, Exploring structured sparsity within data-flow architecture on reconfigurable hardware, Master Physics, Department of Physics and Astronomy, Heidelberg University, supervised by Ulrich Brüning and Holger Fröning, 2021
  15. Benjamin Maier, Comparison of multi-GPU distribution strategies for convolutional neural networks, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2021
  16. Joachim Meyer, Compiler-assisted optimizations for data-parallel paradigms in hipSYCL, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Vincent Heuveline, 2021
  17. Royden Ezra Wagner, Parsing multiple characters of JSON per cycle on FPGAs, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Jonas Dann, 2021
  18. Chenyang Zhu, Comparing performance of GPU and FPGA accelerators using finite element methods, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Vincent Heuveline, 2021
  19. Paul Bethge, Resource-efficient keyword spotting using quantized LSTMs on FPGAs, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Günther Schindler, 2020
  20. Dilan Canpolat, Performance modeling of multi-GPU Communication, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2020
  21. Yannik Emonds, A static analyzer for basic block frequencies, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2020
  22. Michael Harbarth, Compile-time performance modelling for GPGPU kernels using control-flow aware basic-block Analysis, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2019
  23. David Marquant, Exploring the integration of libraries in automated multi-GPU compilation on the example of LU decomposition, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2019
  24. Kevin Stehle, Efficient design and mapping of deep neural networks onto fixed processing units, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2019
  25. Roland Wydra, Visual Odometry for VTOL, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Ulrich Brüning, 2019
  26. Antsa Andriamboavonjy, Evaluating correlations among prediction performance, data complexity, reduced precision, and sparsity of neural networks, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2018
  27. Sven Nobis, Design and evaluation of a communication technique that leverages heterogeneous memory in accelerated clusters, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Robert Strzodka, 2018
  28. Himanshu Tiwari, Supporting and understanding binarized neural networks in Theano, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2018
  29. Andreas Melzer, Compressing sparseternary weight tensors, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2018
  30. Armin Schäffer, Investigating the power saving potential for hierarchical interconnection networks, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Felix Zahn, 2018
  31. Arthur Kühlwein, Hash tables for unordered message matching on SIMT processors, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Benjamin Klenk, 2017
  32. Julian Schwing, Dynamic code generation and execution of user defined logic within graph traversal algorithms, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Michael Gertz, 2017
  33. Lorenz Braun, Code feature supported automated partitioning and communication prediction for multi-GPU applications, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2017
  34. Klaus Naumann, Exploring high-level synthesis for reconfigurable logic to improve time for contemporary machine learning algorithms, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Andreas Kugel, 2017
  35. Dennis Rieber, Characterization of GPU communication, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2017
  36. Dominik Sterk, Optimized bulk data transfer in multi-GPU systems for improved total transfer time, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning and Artur Andrzejak, 2016
  37. Christoph Klein, Automated partitioning of data-parallel programs, Master Physics, Department of Physics and Astronomy, Heidelberg University, supervised by Ulrich Brüning and Holger Fröning, 2016
  38. Benjamin Baumann, A performance model for the training of DNNs on GPUs, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Robert Strzodka, 2016
  39. Steffen Lammel, Demonstrating energy saving potentials for high-performance interconnection networks using a power-aware network simulator, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Felix Zahn, 2016
  40. Eugen Rusakov, Performance monitoring and optimization for Theano-based deep learning on ARM processors, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Andreas Kugel, 2016
  41. Günther Schindler, GPU architecture extensions for advanced communication and synchronization, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2016
  42. Daniel Schlegel, Active messaging in autonomous GPU networks, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning and Robert Strzodka, 2016
  43. Julian Romera, Optimizing communication by compression for multi-GPU scalable breadth-first searches, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2016
  44. Matthias Hauck, Scalable breadth first search using distributed GPUs, Master Applied Computer Science, Department of Computer Science, Heidelberg University, supervised by Holger Fröning, 2013
  45. Benjamin Klenk, Comparing different communication paradigms for data-parallel processors, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2013
  46. Alexander Matz, Extending MEMSCALE by an optimized integration into coherence domains, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2013
  47. Elena Kuss, Analyzing power efficiency and cost effectiveness of direct and indirect interconnetion network topologies, Master Computer Engineering, Institute of Computer Engineering, Heidelberg University, supervised by Holger Fröning, 2012