The ever-increasing demand for scalable database systems is limited by their energy consumption, which is one of the major challenges in research today. While existing approaches mainly focused on transaction-oriented disk-based database systems, we are investigating and optimizing the energy consumption and performance of data-oriented scale-up in-memory database systems that make heavy use of the main power consumers, which are processors and main memory. In this demo, we present energy-utility functions as an approach for enabling the operating system to improve the energy efficiency of scalable in-memory database systems. Our highly interactive demo setup mainly allows attendees to switch between multiple DBMS workloads and watch in detail how the system responds by adapting the hardware configuration appropriately.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:80373 |
Date | 12 August 2022 |
Creators | Kissinger, Thomas, Hähnel, Marcus, Smejkal, Till, Habich, Dirk, Härtig, Hermann, Lehner, Wolfgang |
Publisher | ACM |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
Relation | 978-1-4503-4703-7, 10.1145/3183713.3193554, info:eu-repo/grantAgreement/Deutsche Forschungsgemeinschaft/Sonderforschungsbereiche/164481002//Highly Adaptive Energy-Efficient Computing/HAEC |
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