Lass, M., Kenter, T., Plessl, C., &; Brehm, M. (2024). Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations. Entropy, 26(4), Article 322.https://doi.org/10.3390/e26040322 
LibreCat: /record/53474
DOI: 10.3390/e26040322

Schapeler, T., Schade, R., Lass, M., Plessl, C., &; Bartley, T. (2024). Scalable quantum detector tomography by high-performance computing. In arXiv:2404.02844.
LibreCat: /record/53202
arXiv: 2404.02844

Bauer, C., Kenter, T., Lass, M., Mazur, L., Meyer, M., Nitsche, H., Riebler, H., Schade, R., Schwarz, M., Winnwa, N., Wiens, A., Wu, X., Plessl, C., &; Simon, J. (2024). Noctua 2 Supercomputer. Journal of Large-Scale Research Facilities, 9.https://doi.org/10.17815/jlsrf-8-187  
LibreCat: /record/53663
DOI: 10.17815/jlsrf-8-187 

Schade, R., Kenter, T., Elgabarty, H., Lass, M., Kühne, T., &; Plessl, C. (2023). Breaking the exascale barrier for the electronic structure problem in ab-initio molecular dynamics. The International Journal of High Performance Computing Applications, Article 109434202311776.https://doi.org/10.1177/10943420231177631 
LibreCat: /record/45361
DOI: 10.1177/10943420231177631

Van Hirtum, L., De Causmaecker, P., Goemaere, J., Kenter, T., Riebler, H., Lass, M., &; Plessl, C. (2023). A computation of D(9) using FPGA Supercomputing. In arXiv:2304.03039.
LibreCat: /record/43439
arXiv: 2304.03039

Lass, M. (2022). Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Universität Paderborn.https://doi.org/10.17619/UNIPB/1-1281 
LibreCat: /record/32414
DOI: 10.17619/UNIPB/1-1281

Schade, R., Kenter, T., Elgabarty, H., Lass, M., Schütt, O., Lazzaro, A., Pabst, H., Mohr, S., Hutter, J., Kühne, T., &; Plessl, C. (2022). Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms. Parallel Computing, 111, Article 102920.https://doi.org/10.1016/j.parco.2022.102920 
LibreCat: /record/33684
DOI: 10.1016/j.parco.2022.102920

Kühne, T., Iannuzzi, M., Ben, M. D., Rybkin, V. V., Seewald, P., Stein, F., Laino, T., Khaliullin, R. Z., Schütt, O., Schiffmann, F., Golze, D., Wilhelm, J., Chulkov, S., Mohammad Hossein Bani-Hashemian, M. H. B.-H., Weber, V., Borstnik, U., Taillefumier, M., Jakobovits, A. S., Lazzaro, A.,https://doi.org/10.1063/5.0007045__Hutter, J. (2020). CK: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations. The Journal of Chemical Physics, 152(19), Article 194103.https://doi.org/10.1063/5.0007045 
LibreCat: /record/16277
DOI: 10.1063/5.0007045
arXiv: 2003.03868

Lass, M., Schade, R., Kühne, T., &; Plessl, C. (2020). A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CK. Proc. International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 1127–1140.https://doi.org/10.1109/SC41405.2020.00084 
LibreCat: /record/16898
DOI: 10.1109/SC41405.2020.00084
arXiv: 2004.10811

Rengaraj, V., Lass, M., Plessl, C., &; Kühne, T. (2020). Accurate Sampling with Noisy Forces from Approximate Computing. Computation, 8(2), Article 39.https://doi.org/10.3390/computation8020039 
LibreCat: /record/12878
DOI: 10.3390/computation8020039
arXiv: 1907.08497

Richters, D., Lass, M., Walther, A., Plessl, C., &; Kühne, T. (2019). A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices. Communications in Computational Physics, 25(2), 564–585.https://doi.org/10.4208/cicp.OA-2018-0053 
LibreCat: /record/21
DOI: 10.4208/cicp.OA-2018-0053
arXiv: 1703.02456

Lass, M., Kühne, T., &; Plessl, C. (2018). Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots. Embedded Systems Letters, 10(2), 33–36.https://doi.org/10.1109/LES.2017.2760923 
LibreCat: /record/20
DOI: 10.1109/LES.2017.2760923
arXiv: 1703.02283

Lass, M., Mohr, S., Wiebeler, H., Kühne, T., &; Plessl, C. (2018). 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. Platform for Advanced Scientific Computing Conference (PASC), Basel, Switzerland.https://doi.org/10.1145/3218176.3218231 
LibreCat: /record/1590
DOI: 10.1145/3218176.3218231
arXiv: 1710.10899

Riebler, H., Lass, M., Mittendorf, R., Löcke, T., &; Plessl, C. (2017). Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific Designs. ACM Transactions on Reconfigurable Technology and Systems (TRETS), 10(3), 24:1-24:23.https://doi.org/10.1145/3053687 
LibreCat: /record/18
DOI: 10.1145/3053687

Lass, M., Leibenger, D., &; Sorge, C. (2016). Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension. In Proc. 41st Conference on Local Computer Networks (LCN). IEEE.https://doi.org/10.1109/lcn.2016.11 
LibreCat: /record/19
DOI: 10.1109/lcn.2016.11

Lass, M., Kühne, T., &; Plessl, C. (2016). Using Approximate Computing in Scientific Codes. Workshop on Approximate Computing (AC).
LibreCat: /record/25

Lass, M. (2015). Localization and Analysis of Code Paths Suitable for Acceleration using Approximate Computing. Paderborn: Paderborn University.
LibreCat: /record/1794

Lass, M. (2013). Sichere Speicherung vertraulicher Daten in verteilten Versionskontrollsystemen. Paderborn: Paderborn University.
LibreCat: /record/1795