Daniel Thuerck Head of Development
Qauntum computing - Compilers - Sparse Algorithms - HPC - GPGPU

About me

I am one of the two co-heads of development for Quantagonia, a startup in the excitingly new and innovative world of quantum computing. At Quantagonia, we rely on the collective knowledge of a team of experts from many domains, but focusing on mathematical optimization. We think that mathematical optimization is, in near-term, both a first "killer application" as well as a simple interface to both quantum circuits as well as quantum annealing. In addition to that, we are relying on this insight to construct a compiler that automates porting certain classes of classical x86 code to the quantum domain.

Before leaving academia for Quantagonia, I was a researcher for NEC Labs Europe, Facebook Reality Research, NVIDIA Research and TU Darmstadt. As a PhD student there, I was advised by Prof. Michael Goesele in the GCC group, then by by Prof. Kristian Kersting from the AIML group and Prof. Marc Pfetsch from the Discrete Optimization Group. My research interests were (and are) numerical linear algebra, linear and integer optimization and GPGPU algorithms as well as compilers for heterogeneous systems. While at NEC Research, I took a small detour and devloped my own compiler for batched computational kernels on accelerators called borG as well as several pieces of HPC tools and systems software.

Both in engineering and research (which I do not see as opposites but as both being equally important), I strive to take a systemic approach to problems. Instead of overly optimizing a single component, I try to integrate systems and gain even more from their collaboration In my free time - and whenever possible in my professional life as well - I publish open source code, some of which you'll find linked on this page.

If you're interested in cooperating or just have questions about my research or my projects, don't hesitate to contact me!

Please use my PGP key for secure E-Mail communication.

Curriculum Vitae

ongoing Head of Development - Quantum Systems
04/2022 Quantagonia, Bad Homburg
03/2022 Research Scientist
02/2020 NEC Laboratories Europe, Heidelberg
01/2020 Research Associate / PhD student
08/2015 Graphics, Capture and Massively Parallel Computing (2015 - 2018); Artificial Intelligence and Machine Learning Lab (2018 - 2020), TU Darmstadt
03/2019 Research Intern
09/2018 Facebook Reality Labs, Pittsburgh, under Shoou-I Yu
07/2016 Research Intern
04/2016 NVIDIA Research, PSA group under Michael Garland
03/2016 Research Intern
09/2015 NVIDIA Research, MVC group under Jan Kautz
08/2015 Fast-Track PhD student
10/2014 Graduate School of CE, TU Darmstadt


Conference/Workshop Papers

  • Learning Cuts via Enumeration Oracles

    Daniel Thuerck, Boro Sofranac, Marc E. Pfetsch and Sebastian Pokutta

    NeurIPS 2023, New Orleans, LA, USA, 2023 (accepted)

  • Flynn's reconciliation: Automating the register cache idiom for cross-accelerator programming

    Daniel Thuerck, Nicolas Weber and Roberto Bifulco

    ACM Transactions on Architecture and Code Optimization 18(3), 2021

  • Algorithm 1015: A Fast Scalable Solver for the Dense Linear (Sum) Assignment Problem

    Stefan Guthe and Daniel Thuerck

    ACM Transactions on Mathematical Software 47(2), 2021

  • Supporting Irregularity in Throughput-Oriented Computing by SIMT-SIMD Integration

    Daniel Thuerck

    IEEE/ACM 10th Workshop on Irregular Applications: Architectures and Algorithms (IA3) Short Paper, Virtual Event, 2020

  • Stretching Jacobi: A Two-Stage Pivoting Approach for Block-Based Factorization

    Daniel Thuerck

    IEEE/ACM 9th Workshop on Irregular Applications: Architectures and Algorithms (IA3), Denver, CO, USA, 2019

  • A block-oriented, parallel and collective approach to sparse indefinite preconditioning on GPUs

    Daniel Thuerck, Maxim Naumov, Michael Garland and Michael Goesele

    IEEE/ACM 8th Workshop on Irregular Applications: Architectures and Algorithms (IA3), Dallas, TX, USA, 2018

    Best Paper Award

  • A Fast, Massively Parallel Solver for Large, Irregular Pairwise Markov Random Fields

    Daniel Thuerck, Michael Waechter, Sven Widmer, Max von Buelow, Patrick Seemann, Marc E. Pfetsch and Michael Goesele

    High Performance Graphics (HPG) 2016, Dublin, Ireland, 2016

  • Using graphics processing units to investigate molecular coevolution

    Michael Waechter, Kathrin Jaeger, Daniel Thuerck, Stephanie Weissgraeber, Sven Widmer, Michael Goesele and Kay Hamacher

    Concurrency and Computation: Practice and Experience 26(8), 2014

  • Lazy nonlinear diffusion parameter estimation

    Daniel Thuerck and Arjan Kuijper

    International Conference on Image Analysis and Processing (ICIAP) 2013, Naples, Italy, 2013

  • Efficient heuristic adaptive quadrature on gpus: Design and evaluation

    Daniel Thuerck, Sven Widmer, Arjan Kuijper and Michael Goesele

    International Conference on Parallel Processing and Applied Mathematics (PPAM) 2013, Warsaw, Poland, 2013

  • Nonlinear diffusion at your fingertips: Theory and mobile applications

    Daniel Thuerck and Arjan Kuijper

    2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA), Trieste, Italy, 2013

  • Cosine-driven non-linear denoising

    Daniel Thuerck and Arjan Kuijper

    International Conference Image Analysis and Recognition (ICIAR) 2013, Povoá de Varzim, Portugal, 2013


  • Sparse Matrix Factorization by the Accelerator-First Principle

    SIAM PP, Virtual Event, 2022

  • Finding Parallelism in General-Purpose Linear Programming

    GTC 2017, San José, CA, USA, 2017


  • Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

    PhD Thesis, TU Darmstadt, 2021

  • Optimizing large-scale irregular Markov Random Fields on GPUs

    Master's Thesis, TU Darmstadt, 2014

  • A Well Posed Perona Malik Model and its Implementation Without the Need of Prior Knowledge

    Bachelor's Thesis, TU Darmstadt, 2012

Technical Reports

  • Lock-Free Parallel Feedback Vertex Set Selection

    Daniel Thuerck and Michael Goesele

    TU Darmstadt, 2018