HAEC: Highly Adaptive Energy-Efficient Computing
The mission of the collaborative research center “Highly Adaptive Energy-Efficient Computing” (HAEC) is to enable high energy-efficiency in today’s computing systems without compromising on high performance. The research center covers the circuit level, network level of optical and wireless communication, as well as the software that is needed to operate an adaptive energy-efficient computing platform. The role of the project A04 “Analysis of Applications on a High Performance – Low Energy Computer” is to support the connection between the hardware (group A) and software (group B) projects by providing a simulation infrastructure to allow for simulation-based prediction of performance and energy-efficiency of parallel applications on future parallel computing systems. Furthermore, high quality energy measurements are provided by A04 to other projects in the collaborative research center, while derived energy models will be utilized in the simulation. The simulation infrastructure (HAEC-SIM) developed within HAEC is available for download and described on a separate page: the HAEC simulator.
Collaborative Research Center Website
Project A04 Website
https://tu-dresden.de/ing/forschung/sfb912/Projekte/haec-architecture/document-2011-06-30-8535877175
ZIH Contact
Duration
- 07/2011-06/2015 (Phase I)
- 07/2015-06/2019 (Phase II)
Funding
DFG
Selected Publications
- Thomas Ilsche, Daniel Hackenberg, Robert Schöne, Mario Bielert, Franz Höpfner and Wolfgang E. Nagel. "MetricQ: A Scalable Infrastructure for Processing High-Resolution Time Series Data" In: 2019 IEEE/ACM Industry/University Joint International Workshop on Data-center Automation, Analytics, and Control (DAAC). 2019. https://doi.org/10.1109/DAAC49578.2019.00007
- Robert Schöne, Thomas Ilsche, Mario Bielert, Andreas Gocht, Daniel Hackenberg. "Energy Efficiency Features of the Intel Skylake-SP Processor and Their Impact on Performance" In: 6th Special Session on High Performance Computing Benchmarking and Optimization (HPBench). 2019. (accepted for publication)
- Thomas Ilsche, Robert Schöne, Mario Bielert, Andreas Gocht and Daniel Hackenberg. "lo2s – Multi-Core System and Application Performance Analysis for Linux" In: Workshop on Monitoring and Analysis for High Performance Computing Systems Plus Applications (HPCMASPA). 2017. DOI: 10.1109/CLUSTER.2017.116
- Thomas Ilsche, Marcus Hähnel, Robert Schöne, Mario Bielert and Daniel Hackenberg. "Powernightmares: The Challenge of Efficiently Using Sleep States on Multi-Core Systems" In: 5th Workshop on Runtime and Operating Systems for the Many-core Era (ROME). 2017. https://doi.org/10.1007/978-3-319-75178-8_50
- Mohak Chadha, Thomas Ilsche, Mario Bielert and Wolfgang E. Nagel. "A Statistical Approach to Power Estimation For x86 Processors" In: 13th Workshop on High-Performance, Power-Aware Computing (HPPAC'17). 2017. DOI: 10.1109/IPDPSW.2017.98
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Thomas Ilsche, Robert Schöne, Joseph Schuchart, Daniel Hackenberg, Marc Simon, Yiannis Georgiou and Wolfgang E. Nagel. "Power Measurement Techniques for Energy-Efficient Computing: Reconciling Scalability, Resolution, and Accuracy" In: Second Workshop on Energy-Aware High Performance Computing (EnA-HPC). 2017. DOI: 10.1007/s00450-018-0392-9
- Robert Schöne, Thomas Ilsche, Mario Bielert, Daniel Molka, Daniel Hackenberg. "Software Controlled Clock Modulation for Energy Efficiency Optimization on Intel Processors" In: 4th International Workshop on Energy Efficient Supercomputing (E2SC). 2016. DOI: doi.org/10.1109/E2SC.2016.015
- Joseph Schuchart, Daniel Hackenberg, Robert Schöne, Thomas Ilsche, Ramkumar Nagappan, Michael K. Patterson. “The Shift from Processor Power Consumption to Performance Variations: Fundamental Implications at Scale.” In: First Workshop on Energy-Aware High Performance Computing (EnA-HPC). 2016. DOI: 10.1007/s00450-016-0327-2
- Thomas Ilsche, Daniel Hackenberg, Stefan Graul, Joseph Schuchart, and Robert Schöne. “Power Measurements for Compute Nodes: Improving Sampling Rates, Granularity, and Accuracy.” In: Sixth International Green Computing Conference and Sustainable Computing Conference (IGSC). 2015. DOI: 10.1109/IGCC.2015.7393710
- Mario Bielert, Florina M. Ciorba, Kim Feldhoff, Thomas Ilsche, and Wolfgang E. Nagel. “HAEC-SIM: A Simulation Framework for Highly Adaptive Energy-Efficient Computing Platforms.” In: Eighth Conference on Simulation Tools and Techniques. 2015. DOI: 10.4108/eai.24-8-2015.2261105
- Daniel Hackenberg, Robert Schöne, Thomas Ilsche, Daniel Molka, Joseph Schuchart, and Robin Geyer: An Energy Efficiency Feature Survey of the Intel Haswell Processor. In: 2015 IEEE International Parallel and Distributed Processing Symposium Workshop (IPDPSW). DOI: 10.1109/IPDPSW.2015.70
- Sebastian Götz, Thomas Ilsche, Jorge Cardoso, Josef Spillner, Thomas Kissinger, Uwe Aßmann, Wolfgang Lehner, Wolfgang E. Nagel, and Alexander Schill. “Energy-Efficient Databases Using Sweet Spot Frequencies.” In: 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC 2014). 2014.
- F. M. Ciorba, T. Ilsche, E. Franz, S. Pfennig, C. Scheunert, U. Markwardt, J. Schuchart, D. Hackenberg, R. Schöne, A. Knüpfer, W. E. Nagel, E. A. Jorswieck, and M. S. Müller. “Analysis of Parallel Applications on a High Performance – Low Energy Computer.” In: Euro-Par 2014 Workshops: 7th Workshop on UnConventional High Performance Computing (UCHPC). Vol. 8806. Lecture Notes in Computer Science 03029743. Switzerland: Springer International Publishing, 2014.
- I. Psaroudakis, T. Kissinger, D. Porobic, T. Ilsche, E. Liarou, P. Tözün, A. Ailamaki, and W. Lehner. “Dynamic Fine-Grained Scheduling for Energy-Efficient Main-Memory Queries.” In: 10th International Workshop on Data Management on New Hardware (DaMoN 2014). 2014.
- T. Hilbrich, B. R. de Supinski, W. E. Nagel, J. Protze, C. Baier and M. S. Müller: Distributed wait state tracking for runtime MPI deadlock detection. In: Proceedings of International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2013), Denver, Colorado, November 17-22, 2013.
- D. Hackenberg, T. Ilsche, R. Schoene, D. Molka, M. Schmidt, and W. E. Nagel: Power Measurement Techniques on Standard Compute Nodes: A Quantitative Comparison. In IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS13), Austin, TX USA, April 21-23, 2013.