| Zugriffsnummer | 53370 |
| Dokumenttyp | Konferenzartikel in Zeitschrift |
| Peer Review | mit Peer Review |
| Sprache | Englisch |
| Titel | Developing a digital twin to measure and optimise hpc efficiency |
| Autor(in); Institution |
Kammeyer, Alexander; 9.4, Metrologie für die digitale Transformation, PTB-Berlin
Burger, Florian; Q.45, Hochleistungsrechnen, PTB-Berlin
Lübbert, Daniel; Q.45, Hochleistungsrechnen, PTB-Berlin
Wolter, Katinka; Freie Universität Berlin, Berlin, GERMANY
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| Quelle/Jahr | Proceedings of the XXIV IMEKO World Congress. Measurement: Sensors: 38 (2025), Suppl., e1 - e5 |
| Artikelnummer | 101481 |
| Availability | [online only] |
| ISSN | 2665-9174 (online) |
| DOI | |
| URL | |
| Verlag | Amsterdam [u.a.]: Elsevier |
| Konferenzangaben | IMEKO World Congress 2024, Hamburg, 26-29, August, 2024, Deutschland |
| Freie Schlagworte | HPC ; Data-driven optimisation ; Digital twin ; Energy-aware scheduling ; Data processing |
| Zusammenfassung | A Digital Twin for a high-performance computer requires the integration of many sensors and data sources for monitoring operation and tuning of the system. This paper introduces the network concept for the Digital Twin of PTB's HPC cluster with agents, software components to collect, process and send measurement data to the database of the Digital Twin, and how sensors are separated into networks for security of the data centre. The Digital Twin is used to tune the system for reduced CO2 emissions. In a first step, the focus lies on two control parameters: Processor frequencies, scaled specifically to maximise energy savings, and a modified scheduling mechanism, with deliberate delays helping to exploit phases of low CO2 emissions. In the simulation, frequency scaling showed saving of 3–4 percent and the modified scheduling mechanism, depending on the workload, of 1–9 percent. Combining both methods allowed for savings of up to 11 percent. |
| Kostenfreier Zugang | Open Access Gold |
| Rechteinformation | CC BY 4.0 ; Creative Commons Attribution 4.0 License |