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ORCIDMarkus Höhnerbach
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2020 – today
- 2023
[c7]Harun Bayraktar, Ali Charara, David Clark, Saul Cohen, Timothy B. Costa, Yao-Lung L. Fang, Yang Gao, Jack Guan, John A. Gunnels, Azzam Haidar, Andreas Hehn, Markus Höhnerbach, Matthew Jones, Tom Lubowe, Dmitry I. Lyakh, Shinya Morino, Paul Springer, Sam Stanwyck, Igor Terentyev, Satya Varadhan, Jonathan Wong, Takuma Yamaguchi:
cuQuantum SDK: A High-Performance Library for Accelerating Quantum Science. QCE 2023: 1050-1061- [i7]Harun Bayraktar, Ali Charara, David Clark, Saul Cohen, Timothy B. Costa, Yao-Lung L. Fang, Yang Gao
, Jack Guan, John A. Gunnels, Azzam Haidar, Andreas Hehn, Markus Höhnerbach, Matthew Jones, Tom Lubowe, Dmitry I. Lyakh, Shinya Morino, Paul Springer, Sam Stanwyck, Igor Terentyev, Satya Varadhan, Jonathan Wong, Takuma Yamaguchi:
cuQuantum SDK: A High-Performance Library for Accelerating Quantum Science. CoRR abs/2308.01999 (2023) - 2020
- [b1]Markus Höhnerbach:
A framework for the vectorization of molecular dynamics kernels. RWTH Aachen University, Germany, 2020
2010 – 2019
- 2019
- [j2]Markus Höhnerbach, Paolo Bientinesi:
Accelerating AIREBO: Navigating the Journey from Legacy to High-Performance Code. J. Comput. Chem. 40(14): 1471-1482 (2019) - 2018
- [j1]Davor Davidovic, Diego Fabregat-Traver, Markus Höhnerbach, Edoardo Di Napoli:
Accelerating the computation of FLAPW methods on heterogeneous architectures. Concurr. Comput. Pract. Exp. 30(24) (2018) - [i6]Markus Höhnerbach, Paolo Bientinesi:
Optimizing AIREBO: Navigating the Journey from Complex Legacy Code to High Performance. CoRR abs/1810.07026 (2018) - 2017
- [c6]William McDoniel, Markus Höhnerbach, Rodrigo Canales, Ahmed E. Ismail, Paolo Bientinesi:
LAMMPS' PPPM Long-Range Solver for the Second Generation Xeon Phi. ISC 2017: 61-78 - [i5]William McDoniel, Markus Höhnerbach, Rodrigo Canales, Ahmed E. Ismail, Paolo Bientinesi:
LAMMPS' PPPM Long-Range Solver for the Second Generation Xeon Phi. CoRR abs/1702.04250 (2017) - [i4]Markus Höhnerbach, Ahmed E. Ismail, Paolo Bientinesi:
The Tersoff many-body potential: Sustainable performance through vectorization. CoRR abs/1710.00882 (2017) - [i3]Davor Davidovic, Diego Fabregat-Traver, Markus Höhnerbach, Edoardo Di Napoli:
Accelerating the computation of FLAPW methods on heterogeneous architectures. CoRR abs/1712.07206 (2017) - 2016
- [c5]Diego Fabregat-Traver, Davor Davidovic, Markus Höhnerbach, Edoardo Di Napoli:
Hybrid CPU-GPU Generation of the Hamiltonian and Overlap Matrices in FLAPW Methods. JHPCS 2016: 200-211 - [c4]Markus Höhnerbach, Ahmed E. Ismail, Paolo Bientinesi:
The vectorization of the tersoff multi-body potential: an exercise in performance portability. SC 2016: 69-81 - [c3]Olaf Krzikalla, Florian Wende, Markus Höhnerbach:
Dynamic SIMD Vector Lane Scheduling. ISC Workshops 2016: 354-365 - [i2]Markus Höhnerbach, Ahmed E. Ismail, Paolo Bientinesi:
The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability. CoRR abs/1607.02904 (2016) - [i1]Diego Fabregat-Traver, Davor Davidovic, Markus Höhnerbach, Edoardo Di Napoli:
Hybrid CPU-GPU generation of the Hamiltonian and Overlap matrices in FLAPW methods. CoRR abs/1611.00606 (2016) - 2014
- [c2]Christoph Beierle, Markus Höhnerbach, Marcus Marto:
Generation of Parametrically Uniform Knowledge Bases in a Relational Probabilistic Logic with Maximum Entropy Semantics. PRUV 2014: 39-51 - [c1]Christoph Beierle, Markus Höhnerbach, Marcus Marto:
Implementation of a Transformation System for Relational Probabilistic Knowledge Bases Simplifying the Maximum Entropy Model Computation. FLAIRS 2014
Coauthor Index
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