M. Lass, Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations. Paderborn: Universität Paderborn, 2022.

R. Schade et al., “Towards electronic structure-based ab-initio molecular dynamics simulations with hundreds of millions of atoms,”10.1016/j.parco.2022.102920__Parallel Computing, vol. 111, Art. no. 102920, 2022, doi:10.1016/j.parco.2022.102920 .

T. Kühne et al., “CK: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations,”10.1063/5.0007045__The Journal of Chemical Physics, vol. 152, no. 19, Art. no. 194103, 2020, doi:10.1063/5.0007045 .

M. Lass, R. Schade, T. Kühne, and C. Plessl, “A Submatrix-Based Method for Approximate Matrix Function Evaluation in the Quantum Chemistry Code CK,”10.1109/SC41405.2020.00084__in Proc. International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, 2020, pp. 1127–1140, doi:10.1109/SC41405.2020.00084 .

V. Rengaraj, M. Lass, C. Plessl, and T. Kühne, “Accurate Sampling with Noisy Forces from Approximate Computing,”10.3390/computation8020039__Computation, vol. 8, no. 2, Art. no. 39, 2020, doi:10.3390/computation8020039 .

D. Richters, M. Lass, A. Walther, C. Plessl, and T. Kühne, “A General Algorithm to Calculate the Inverse Principal p-th Root of Symmetric Positive Definite Matrices,”10.4208/cicp.OA-2018-0053__Communications in Computational Physics, vol. 25, no. 2, pp. 564–585, 2019, doi:10.4208/cicp.OA-2018-0053 .

M. Lass, T. Kühne, and C. Plessl, “Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots,” Embedded Systems Letters, vol. 10, no. 2, pp. 33–36, 2018.

M. Lass, S. Mohr, H. Wiebeler, T. Kühne, and C. Plessl, “A Massively Parallel Algorithm for the Approximate Calculation of Inverse p-th Roots of Large Sparse Matrices,”10.1145/3218176.3218231__presented at the Platform for Advanced Scientific Computing Conference (PASC), Basel, Switzerland, 2018, doi:10.1145/3218176.3218231 .

H. Riebler, M. Lass, R. Mittendorf, T. Löcke, and C. Plessl, “Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific Designs,”10.1145/3053687__ACM Transactions on Reconfigurable Technology and Systems (TRETS), vol. 10, no. 3, p. 24:1-24:23, 2017, doi:10.1145/3053687 .

M. Lass, D. Leibenger, and C. Sorge, “Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension,” in Proc. 41st Conference on Local Computer Networks (LCN), 2016.

M. Lass, T. Kühne, and C. Plessl, “Using Approximate Computing in Scientific Codes,” 2016.

M. Lass, Localization and Analysis of Code Paths Suitable for Acceleration using Approximate Computing. Paderborn: Paderborn University, 2015.

M. Lass, Sichere Speicherung vertraulicher Daten in verteilten Versionskontrollsystemen. Paderborn: Paderborn University, 2013.