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Michael Knobloch
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2020 – today
- 2023
- [c11]Joachim Jenke
, Michael Knobloch
A Shim Layer for Transparently Adding Meta Data to MPI Handles. EuroMPI 2023: 6:1-6:9 - 2022
- [c10]Elvis Rojas, Michael Knobloch, Nour Daoud, Esteban Meneses, Bernd Mohr:
Early Experiences of Noise-Sensitivity Performance Analysis of a Distributed Deep Learning Framework. CLUSTER 2022: 516-522 - 2020
- [j8]Michael Knobloch, Bernd Mohr:
Tools for GPU Computing - Debugging and Performance Analysis of Heterogenous HPC Applications. Supercomput. Front. Innov. 7(1): 91-111 (2020)
2010 – 2019
- 2019
- [j7]Marc-André Hermanns
The MPI_T events interface: An early evaluation and overview of the interface. Parallel Comput. 85: 119-130 (2019) - [i1]Robert Speck, Michael Knobloch, Andreas Gocht, Sebastian Lührs:
Using performance analysis tools for parallel-in-time integrators - Does my time-parallel code do what I think it does? CoRR abs/1911.13027 (2019) - 2018
- [c9]Marc-André Hermanns
Enabling callback-driven runtime introspection via MPI_T. EuroMPI 2018: 8:1-8:10 - 2015
- [c8]Christian Iwainsky, Sergei Shudler
How Many Threads will be too Many? On the Scalability of OpenMP Implementations. Euro-Par 2015: 451-463 - [c7]Pavel Saviankou
Cube v4: From Performance Report Explorer to Performance Analysis Tool. ICCS 2015: 1343-1352 - 2014
- [j6]Michael Knobloch
Mapping fine-grained power measurements to HPC application runtime characteristics on IBM POWER7. Comput. Sci. Res. Dev. 29(3-4): 211-219 (2014) - [j5]Robert Schöne, Jan Treibig, Manuel F. Dolz
Tools and methods for measuring and tuning the energy efficiency of HPC systems. Sci. Program. 22(4): 273-283 (2014) - [c6]Jie Jiang, Peter Philippen, Michael Knobloch
Performance Measurement and Analysis of Transactional Memory and Speculative Execution on IBM Blue Gene/Q. Euro-Par 2014: 26-37 - [c5]Philipp Gschwandtner
Modeling CPU Energy Consumption of HPC Applications on the IBM POWER7. PDP 2014: 536-543 - 2013
- [j4]Michael Knobloch:
Energy-Aware High Performance Computing - A Survey. Adv. Comput. 88: 1-78 (2013) - [j3]Sadaf R. Alam, Constantine Bekas, Hans Boettiger, Alessandro Curioni, Gilles Fourestey, Willi Homberg, Michael Knobloch
Early experiences with scientific applications on the IBM Blue Gene/Q supercomputer. IBM J. Res. Dev. 57(1/2): 14 (2013) - [c4]Paul F. Baumeister
Characterizing Performance of Applications on Blue Gene/Q. PARCO 2013: 113-122 - 2012
- [j2]Michael Knobloch
Determine energy-saving potential in wait-states of large-scale parallel programs. Comput. Sci. Res. Dev. 27(4): 255-263 (2012) - [j1]Michael Hennecke
Measuring power consumption on IBM Blue Gene/P. Comput. Sci. Res. Dev. 27(4): 329-336 (2012) - [r1]Timo Minartz, Daniel Molka, Julian M. Kunkel, Michael Knobloch, Michael Kuhn, Thomas Ludwig:
Tool Environments to Measure Power Consumption and Computational Performance. Handbook of Energy-Aware and Green Computing 2012: 709-744 - 2011
- [c3]Timo Minartz, Thomas Ludwig, Michael Knobloch
Managing hardware power saving modes for high performance computing. IGCC 2011: 1-8 - [c2]Michael Knobloch, Timo Minartz, Daniel Molka, Stephan Krempel, Thomas Ludwig, Bernd Mohr:
Electronic poster: eeclust: energy-efficient cluster computing. SC Companion 2011: 99-100 - 2010
- [c1]Timo Minartz, Daniel Molka, Michael Knobloch
eeClust: Energy-Efficient Cluster Computing. CHPC 2010: 111-124
Coauthor Index
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