Zur Kurzanzeige

dc.contributor.authorNoll, Stefan
dc.contributor.authorFunke, Henning
dc.contributor.authorTeubner, Jens
dc.date2017-11-01
dc.date.accessioned2018-01-08T08:08:00Z
dc.date.available2018-01-08T08:08:00Z
dc.date.issued2017
dc.identifier.issn1610-1995
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/11016
dc.description.abstractAs the operating costs of today’s data centres continue to increase and processor manufacturers are forced to meet thermal design power constraints when designing new hardware, the energy efficiency of a main-memory database management system becomes more and more important. Plus, lots of database workloads are more memory-intensive than compute-intensive, which results in computing power being unused and wasted. This can become a problem because wasting computing also means wasting electrical power.In this paper, we experimentally study the impact of reducing the clock frequency of the processor and the impact of using fewer processor cores on the energy efficiency of common database algorithms such as scans, simple aggregations, simple hash joins, and state-of-the-art join algorithms. We stress the fundamental trade-off between peak performance and energy efficiency, as opposed to the established race-to-idle strategy. Ultimately, we show that reducing unused computing power significantly improves the energy efficiency of memory-bound database algorithms.
dc.publisherSpringer
dc.relation.ispartofDatenbank-Spektrum: Vol. 17, No. 3
dc.relation.ispartofseriesDatenbank-Spektrum
dc.titleEnergy Efficiency in Main-Memory Databases
dc.typeText/Journal Article
mci.reference.pages223-232
gi.identifier.doi10.1007/s13222-017-0262-9


Dateien zu dieser Ressource

DateienGrößeFormatAnzeige

Zu diesem Dokument gibt es keine Dateien.

Zur Kurzanzeige