Michael Lass

According to our database, Michael Lass authored at least 16 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Computation of the Ninth Dedekind Number Using FPGA Supercomputing.

Lennart Van Hirtum, Patrick De Causmaecker, Jens Goemaere, Tobias Kenter, Heinrich Riebler, Michael Lass, Christian Plessl

ACM Trans. Reconfigurable Technol. Syst., September, 2024

Characterizing Microheterogeneity in Liquid Mixtures via Local Density Fluctuations.

Michael Lass, Tobias Kenter, Christian Plessl, Martin Brehm

Entropy, April, 2024

Scalable quantum detector tomography by high-performance computing.

Timon Schapeler, Robert Schade, Michael Lass, Christian Plessl, Tim J. Bartley

CoRR, 2024

2023

Breaking the exascale barrier for the electronic structure problem in <i>ab-initio</i> molecular dynamics.

Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Thomas D. Kühne, Christian Plessl

Int. J. High Perform. Comput. Appl., September, 2023

A computation of D(9) using FPGA Supercomputing.

Lennart Van Hirtum, Patrick De Causmaecker, Jens Goemaere, Tobias Kenter, Heinrich Riebler, Michael Lass, Christian Plessl

CoRR, 2023

2022

Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations.

Michael Lass

PhD thesis, 2022

Towards electronic structure-based <i>ab-initio</i> molecular dynamics simulations with hundreds of millions of atoms.

Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt, Alfio Lazzaro, Hans Pabst, Stephan Mohr, Jürg Hutter, Thomas D. Kühne, Christian Plessl

Parallel Comput., 2022

2021

Enabling Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms.

Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt, Alfio Lazzaro, Hans Pabst, Stephan Mohr, Jürg Hutter, Thomas D. Kühne, Christian Plessl

CoRR, 2021

2020

Accurate Sampling with Noisy Forces from Approximate Computing.

Varadarajan Rengaraj, Michael Lass, Christian Plessl, Thomas D. Kühne

Comput., 2020

A submatrix-based method for approximate matrix function evaluation in the quantum chemistry code CP2K.

Michael Lass, Robert Schade, Thomas D. Kühne, Christian Plessl

Proceedings of the International Conference for High Performance Computing, 2020

2018

Using Approximate Computing for the Calculation of Inverse Matrix <i>p</i>th Roots.

Michael Lass, Thomas D. Kühne, Christian Plessl

IEEE Embed. Syst. Lett., 2018

A Massively Parallel Algorithm for the Approximate Calculation of Inverse p-th Roots of Large Sparse Matrices.

Michael Lass, Stephan Mohr, Hendrik Wiebeler, Thomas D. Kühne, Christian Plessl

Proceedings of the Platform for Advanced Scientific Computing Conference, 2018

2017

Efficient Branch and Bound on FPGAs Using Work Stealing and Instance-Specific Designs.

Heinrich Riebler, Michael Lass, Robert Mittendorf, Thomas Löcke, Christian Plessl

ACM Trans. Reconfigurable Technol. Syst., 2017

A Massively Parallel Algorithm for the Approximate Calculation of Inverse p-th Roots of Large Sparse Matrices.

Michael Lass, Stephan Mohr, Thomas D. Kühne, Christian Plessl

CoRR, 2017

Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots.

Michael Lass, Thomas D. Kühne, Christian Plessl

CoRR, 2017

2016

Confidentiality and Authenticity for Distributed Version Control Systems - A Mercurial Extension.

Michael Lass, Dominik Leibenger, Christoph Sorge

Proceedings of the 41st IEEE Conference on Local Computer Networks, 2016