Michael Laß
Paderborn Center for Parallel Computing (PC2)
Hochleistungsrechnen
michael.lass@uni-paderborn.deID
19 Publications
2025 | Journal Article | LibreCat-ID: 53202 |

Schapeler, Timon, et al. “Scalable Quantum Detector Tomography by High-Performance Computing.” Quantum Science and Technology, vol. 10, no. 1, IOP Publishing, 2025, doi:10.1088/2058-9565/ad8511.
LibreCat
| DOI
| Download (ext.)
| arXiv
2024 | Journal Article | LibreCat-ID: 53474
Lass, Michael, et al. “Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations.” Entropy, vol. 26, no. 4, 322, MDPI AG, 2024, doi:10.3390/e26040322.
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 53663 |

Bauer, Carsten, et al. “Noctua 2 Supercomputer.” Journal of Large-Scale Research Facilities, vol. 9, 2024, doi:10.17815/jlsrf-8-187 .
LibreCat
| Files available
| DOI
2024 | Journal Article | LibreCat-ID: 56604 |

Van Hirtum, Lennart, et al. “A Computation of the Ninth Dedekind Number Using FPGA Supercomputing.” ACM Transactions on Reconfigurable Technology and Systems, vol. 17, no. 3, Association for Computing Machinery (ACM), 2024, pp. 1–28, doi:10.1145/3674147.
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| DOI
| Download (ext.)
2023 | Journal Article | LibreCat-ID: 45361 |

Schade, Robert, et al. “Breaking the Exascale Barrier for the Electronic Structure Problem in Ab-Initio Molecular Dynamics.” The International Journal of High Performance Computing Applications, 109434202311776, SAGE Publications, 2023, doi:10.1177/10943420231177631.
LibreCat
| DOI
| Download (ext.)
2022 | Dissertation | LibreCat-ID: 32414
Lass, Michael. Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Universität Paderborn, 2022, doi:10.17619/UNIPB/1-1281.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 33684 |

Schade, Robert, et al. “Towards Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms.” Parallel Computing, vol. 111, 102920, Elsevier BV, 2022, doi:10.1016/j.parco.2022.102920.
LibreCat
| DOI
| Download (ext.)
2020 | Journal Article | LibreCat-ID: 16277 |

Kühne, Thomas, et al. “CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations.” The Journal of Chemical Physics, vol. 152, no. 19, 194103, 2020, doi:10.1063/5.0007045.
LibreCat
| Files available
| DOI
| Download (ext.)
| arXiv
2020 | Conference Paper | LibreCat-ID: 16898
Lass, Michael, et al. “A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CP2K.” Proc. International Conference for High Performance Computing, Networking, Storage and Analysis (SC), IEEE Computer Society, 2020, pp. 1127–40, doi:10.1109/SC41405.2020.00084.
LibreCat
| DOI
| Download (ext.)
| arXiv
2020 | Journal Article | LibreCat-ID: 12878 |

Rengaraj, Varadarajan, et al. “Accurate Sampling with Noisy Forces from Approximate Computing.” Computation, vol. 8, no. 2, 39, MDPI, 2020, doi:10.3390/computation8020039.
LibreCat
| DOI
| Download (ext.)
| arXiv
2019 | Journal Article | LibreCat-ID: 21
Richters, Dorothee, et al. “A General Algorithm to Calculate the Inverse Principal P-Th Root of Symmetric Positive Definite Matrices.” Communications in Computational Physics, vol. 25, no. 2, Global Science Press, 2019, pp. 564–85, doi:10.4208/cicp.OA-2018-0053.
LibreCat
| DOI
| arXiv
2018 | Journal Article | LibreCat-ID: 20
Lass, Michael, et al. “Using Approximate Computing for the Calculation of Inverse Matrix P-Th Roots.” Embedded Systems Letters, vol. 10, no. 2, IEEE, 2018, pp. 33–36, doi:10.1109/LES.2017.2760923.
LibreCat
| DOI
| arXiv
2018 | Conference Paper | LibreCat-ID: 1590
Lass, Michael, et al. “A Massively Parallel Algorithm for the Approximate Calculation of Inverse P-Th Roots of Large Sparse Matrices.” Proc. Platform for Advanced Scientific Computing (PASC) Conference, ACM, 2018, doi:10.1145/3218176.3218231.
LibreCat
| DOI
| arXiv
2017 | Journal Article | LibreCat-ID: 18
Riebler, Heinrich, et al. “Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific Designs.” ACM Transactions on Reconfigurable Technology and Systems (TRETS), vol. 10, no. 3, Association for Computing Machinery (ACM), 2017, p. 24:1-24:23, doi:10.1145/3053687.
LibreCat
| Files available
| DOI
2016 | Conference Paper | LibreCat-ID: 19
Lass, Michael, et al. “Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension.” Proc. 41st Conference on Local Computer Networks (LCN), IEEE, 2016, doi:10.1109/lcn.2016.11.
LibreCat
| DOI
2016 | Conference Paper | LibreCat-ID: 25
Lass, Michael, et al. “Using Approximate Computing in Scientific Codes.” Workshop on Approximate Computing (AC), 2016.
LibreCat
2015 | Mastersthesis | LibreCat-ID: 1794
Lass, Michael. Localization and Analysis of Code Paths Suitable for Acceleration Using Approximate Computing. Paderborn University, 2015.
LibreCat
2013 | Bachelorsthesis | LibreCat-ID: 1795
Lass, Michael. Sichere Speicherung Vertraulicher Daten in Verteilten Versionskontrollsystemen. Paderborn University, 2013.
LibreCat
19 Publications
2025 | Journal Article | LibreCat-ID: 53202 |

Schapeler, Timon, et al. “Scalable Quantum Detector Tomography by High-Performance Computing.” Quantum Science and Technology, vol. 10, no. 1, IOP Publishing, 2025, doi:10.1088/2058-9565/ad8511.
LibreCat
| DOI
| Download (ext.)
| arXiv
2024 | Journal Article | LibreCat-ID: 53474
Lass, Michael, et al. “Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations.” Entropy, vol. 26, no. 4, 322, MDPI AG, 2024, doi:10.3390/e26040322.
LibreCat
| DOI
2024 | Journal Article | LibreCat-ID: 53663 |

Bauer, Carsten, et al. “Noctua 2 Supercomputer.” Journal of Large-Scale Research Facilities, vol. 9, 2024, doi:10.17815/jlsrf-8-187 .
LibreCat
| Files available
| DOI
2024 | Journal Article | LibreCat-ID: 56604 |

Van Hirtum, Lennart, et al. “A Computation of the Ninth Dedekind Number Using FPGA Supercomputing.” ACM Transactions on Reconfigurable Technology and Systems, vol. 17, no. 3, Association for Computing Machinery (ACM), 2024, pp. 1–28, doi:10.1145/3674147.
LibreCat
| DOI
| Download (ext.)
2023 | Journal Article | LibreCat-ID: 45361 |

Schade, Robert, et al. “Breaking the Exascale Barrier for the Electronic Structure Problem in Ab-Initio Molecular Dynamics.” The International Journal of High Performance Computing Applications, 109434202311776, SAGE Publications, 2023, doi:10.1177/10943420231177631.
LibreCat
| DOI
| Download (ext.)
2022 | Dissertation | LibreCat-ID: 32414
Lass, Michael. Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Universität Paderborn, 2022, doi:10.17619/UNIPB/1-1281.
LibreCat
| DOI
2022 | Journal Article | LibreCat-ID: 33684 |

Schade, Robert, et al. “Towards Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms.” Parallel Computing, vol. 111, 102920, Elsevier BV, 2022, doi:10.1016/j.parco.2022.102920.
LibreCat
| DOI
| Download (ext.)
2020 | Journal Article | LibreCat-ID: 16277 |

Kühne, Thomas, et al. “CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations.” The Journal of Chemical Physics, vol. 152, no. 19, 194103, 2020, doi:10.1063/5.0007045.
LibreCat
| Files available
| DOI
| Download (ext.)
| arXiv
2020 | Conference Paper | LibreCat-ID: 16898
Lass, Michael, et al. “A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CP2K.” Proc. International Conference for High Performance Computing, Networking, Storage and Analysis (SC), IEEE Computer Society, 2020, pp. 1127–40, doi:10.1109/SC41405.2020.00084.
LibreCat
| DOI
| Download (ext.)
| arXiv
2020 | Journal Article | LibreCat-ID: 12878 |

Rengaraj, Varadarajan, et al. “Accurate Sampling with Noisy Forces from Approximate Computing.” Computation, vol. 8, no. 2, 39, MDPI, 2020, doi:10.3390/computation8020039.
LibreCat
| DOI
| Download (ext.)
| arXiv
2019 | Journal Article | LibreCat-ID: 21
Richters, Dorothee, et al. “A General Algorithm to Calculate the Inverse Principal P-Th Root of Symmetric Positive Definite Matrices.” Communications in Computational Physics, vol. 25, no. 2, Global Science Press, 2019, pp. 564–85, doi:10.4208/cicp.OA-2018-0053.
LibreCat
| DOI
| arXiv
2018 | Journal Article | LibreCat-ID: 20
Lass, Michael, et al. “Using Approximate Computing for the Calculation of Inverse Matrix P-Th Roots.” Embedded Systems Letters, vol. 10, no. 2, IEEE, 2018, pp. 33–36, doi:10.1109/LES.2017.2760923.
LibreCat
| DOI
| arXiv
2018 | Conference Paper | LibreCat-ID: 1590
Lass, Michael, et al. “A Massively Parallel Algorithm for the Approximate Calculation of Inverse P-Th Roots of Large Sparse Matrices.” Proc. Platform for Advanced Scientific Computing (PASC) Conference, ACM, 2018, doi:10.1145/3218176.3218231.
LibreCat
| DOI
| arXiv
2017 | Journal Article | LibreCat-ID: 18
Riebler, Heinrich, et al. “Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific Designs.” ACM Transactions on Reconfigurable Technology and Systems (TRETS), vol. 10, no. 3, Association for Computing Machinery (ACM), 2017, p. 24:1-24:23, doi:10.1145/3053687.
LibreCat
| Files available
| DOI
2016 | Conference Paper | LibreCat-ID: 19
Lass, Michael, et al. “Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension.” Proc. 41st Conference on Local Computer Networks (LCN), IEEE, 2016, doi:10.1109/lcn.2016.11.
LibreCat
| DOI
2016 | Conference Paper | LibreCat-ID: 25
Lass, Michael, et al. “Using Approximate Computing in Scientific Codes.” Workshop on Approximate Computing (AC), 2016.
LibreCat
2015 | Mastersthesis | LibreCat-ID: 1794
Lass, Michael. Localization and Analysis of Code Paths Suitable for Acceleration Using Approximate Computing. Paderborn University, 2015.
LibreCat
2013 | Bachelorsthesis | LibreCat-ID: 1795
Lass, Michael. Sichere Speicherung Vertraulicher Daten in Verteilten Versionskontrollsystemen. Paderborn University, 2013.
LibreCat