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Matthias Maiterth
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Practical resource management in power-constrained, high performance computing
T Patki, DK Lowenthal, A Sasidharan, M Maiterth, BL Rountree, M Schulz, ...
Proceedings of the 24th international symposium on high-performance parallel …, 2015
1102015
Global extensible open power manager: a vehicle for HPC community collaboration on co-designed energy management solutions
J Eastep, S Sylvester, C Cantalupo, B Geltz, F Ardanaz, A Al-Rawi, ...
International Conference on High Performance Computing, 394-412, 2017
812017
DASH: Data structures and algorithms with support for hierarchical locality
K Fürlinger, C Glass, J Gracia, A Knüpfer, J Tao, D Hünich, K Idrees, ...
European Conference on Parallel Processing, 542-552, 2014
532014
Energy and power aware job scheduling and resource management: Global survey—initial analysis
M Maiterth, G Koenig, K Pedretti, S Jana, N Bates, A Borghesi, D Montoya, ...
2018 IEEE International Parallel and Distributed Processing Symposium …, 2018
342018
Power aware high performance computing: Challenges and opportunities for application and system developers—Survey & tutorial
M Maiterth, T Wilde, D Lowenthal, B Rountree, M Schulz, J Eastep, ...
2017 International Conference on High Performance Computing & Simulation …, 2017
122017
Power balancing in an emulated exascale environment
M Maiterth, M Schulz, D Kranzlmüller, B Rountree
2016 IEEE International Parallel and Distributed Processing Symposium …, 2016
92016
Towards a predictive energy model for HPC runtime systems using supervised learning
G Ozer, S Garg, N Davoudi, G Poerwawinata, M Maiterth, A Netti, D Tafani
European Conference on Parallel Processing, 626-638, 2019
82019
A strawman for an hpc powerstack
C Cantalupo, J Eastep, S Jana, M Kondo, M Maiterth, A Marathe, T Patki, ...
Intel Corporation (United States); Lawrence Livermore National Lab.(LLNL …, 2018
32018
Energy-efficient runtime in HPC systems with machine learning
G Ozer, S Garg, G Poerwawinata, N Davoudi, MDT LRZ, M Maiterth, ...
Technical University of Munich, Data Innovation Lab, 2019
22019
Global Survey of Energy and Power-aware Job Scheduling and Resource Management in Supercomputing Centers
S Jana, GA Koenig, M Maiterth, KT Pedretti, A Borghesi, A Bartolini, ...
22017
Scalability under a Power Bound using the GREMLINs Framework
M Maiterth
Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2015
22015
Parallel Datalog on Pregel
M Maiterth
Institut fur Informatik der Ludwig-Maximilians-Universitat Munchen, 2012
22012
Energy and Power Aware Job Scheduling and Resource Management: Global Survey—An In-Depth Analysis
GA Koenig, M Maiterth, S Jana, N Bates, K Pedretti, M Puzovic, ...
The 2nd International Industry/University Workshop on Data-center Automation …, 0
1
A reference model for integrated energy and power management of HPC systems
M Maiterth
lmu, 2021
2021
Energy and Job Scheduling and Resource Management: Global Survey --- An In-Depth Analysis
GA Koenig, M Maiterth, S Jana, N Bates, K Pedretti, M Puzovic, ...
The 2nd International Industry/University Workshop on Data-center Automation …, 2018
2018
Energy and Power Aware Job Scheduling and Resource Management: Global Survey?.
G Koenig, M Maiterth, S Jana, N Bates, K Pedretti, M Puzovic, A Borghesi, ...
Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2018
2018
EE HPC SOP 2021 Conference Organization
N Bates, S Jana, T Wilde, AM Bailey, C Deprater, D Grant, D Martinez, ...
ISPDC 2015 Reviewers
M Jawad, N Sukhija, J Zhou, S Soner, M Maiterth, D Antão, G Buse, D Dai, ...
HPCS 2017
D Kranzlmüller, M Maiterth, T Wilde
HPCS 2017
M Maiterth, T Wilde, D Lowenthal, B Rountree, M Schulz, J Eastep, ...
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