Markus Eisenbach

Orcid: 0000-0001-8805-8327

Affiliations:
  • Oak Ridge National Laboratory, TN, USA


According to our database1, Markus Eisenbach authored at least 26 papers between 2006 and 2024.

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Bibliography

2024
Transferring predictions of formation energy across lattices of increasing size.
Mach. Learn. Sci. Technol., 2024

Integrating quantum computing resources into scientific HPC ecosystems.
Future Gener. Comput. Syst., 2024

2023
Experiences Readying Applications for Exascale.
CoRR, 2023

Ready for the Frontier: Preparing Applications for the World's First Exascale System.
Proceedings of the High Performance Computing - 38th International Conference, 2023



2022
OpenMP application experiences: Porting to accelerated nodes.
Parallel Comput., 2022

Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials.
Proceedings of the Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, 2022

Learning to Scale the Summit: AI for Science on a Leadership Supercomputer.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

2021
A scalable algorithm for the optimization of neural network architectures.
Parallel Comput., 2021

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

2020
Integrating Deep Learning in Domain Sciences at Exascale.
Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

2019
Error controlling of the combined Cluster-Expansion and Wang-Landau Monte-Carlo method and its application to FeCo.
Comput. Phys. Commun., 2019

Histogram-free multicanonical Monte Carlo sampling to calculate the density of states.
Comput. Phys. Commun., 2019

A greedy constructive algorithm for the optimization of neural network architectures.
CoRR, 2019

2018
Fully-relativistic full-potential multiple scattering theory: A pathology-free scheme.
Comput. Phys. Commun., 2018

2017
Large-Scale Calculations for Material Sciences Using Accelerators to Improve Time- and Energy-to-Solution.
Comput. Sci. Eng., 2017

Acceleration of the Particle Swarm Optimization for Peierls-Nabarro modeling of dislocations in conventional and high-entropy alloys.
Comput. Phys. Commun., 2017

GPU acceleration of the Locally Selfconsistent Multiple Scattering code for first principles calculation of the ground state and statistical physics of materials.
Comput. Phys. Commun., 2017

A Histogram-Free Multicanonical Monte Carlo Algorithm for the Basis Expansion of Density of States.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2017

2015
Accelerated application development: The ORNL Titan experience.
Comput. Electr. Eng., 2015

CUDA Grid-Level Task Progression Algorithms.
Proceedings of the 17th IEEE International Conference on High Performance Computing and Communications, 2015

2013
Toward Abstracting the Communication Intent in Applications to Improve Portability and Productivity.
Proceedings of the 2013 IEEE International Symposium on Parallel & Distributed Processing, 2013

2009
A scalable method for <i>ab initio</i> computation of free energies in nanoscale systems.
Proceedings of the ACM/IEEE Conference on High Performance Computing, 2009

2008
New algorithm to enable 400+ TFlop/s sustained performance in simulations of disorder effects in high-<i>T</i><sub>c</sub> superconductors.
Proceedings of the ACM/IEEE Conference on High Performance Computing, 2008

2006
Teraflop Computing for Nanoscience.
Proceedings of the 2006 International Conference on Computer Design & Conference on Computing in Nanotechnology, 2006


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