NeMeSys - Energy adaptive graph pattern matching on numa-based multiprocessor systems
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
NeMeSys is a NUMA-aware graph pattern processing engine, which leverages intelligent resource management for energy adaptive processing. With modern server systems incorporating an increasing amount of main memory, we can store graphs and compute analytical graph algorithms like graph pattern matching completely in-memory. Such server systems usually contain several powerful multiprocessors, which come with a high demand for energy. We demonstrate, that graph patterns can be processed in given performance constraints while saving energy, which would be wasted without proper controlling.
Details
Originalsprache | Englisch |
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Titel | Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019 |
Redakteure/-innen | Torsten Grust, Felix Naumann, Alexander Bohm, Wolfgang Lehner, Theo Harder, Erhard Rahm, Andreas Heuer, Meike Klettke, Holger Meyer |
Herausgeber (Verlag) | Gesellschaft fur Informatik (GI) |
Seiten | 537-541 |
Seitenumfang | 5 |
ISBN (elektronisch) | 9783885796831 |
Publikationsstatus | Veröffentlicht - 2019 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | GI-Edition : lecture notes in informatics. Proceedings |
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Band | P-289 |
ISSN | 1617-5468 |
Konferenz
Titel | Datenbanksysteme fur Business, Technologie und Web, BTW 2019 and 18. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme", DBIS 2019 - Database Systems for Business, Technology and Web, BTW 2019 and 18th Symposium of the GI Department "Databases and Information Systems", DBIS 2019 |
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Dauer | 4 - 8 März 2019 |
Stadt | Rostock |
Land | Deutschland |
Externe IDs
dblp | conf/btw/KrauseUKHL19 |
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ORCID | /0000-0001-8107-2775/work/142253494 |
Schlagworte
ASJC Scopus Sachgebiete
Schlagwörter
- Adaptivity, Energy, Graph, NUMA, Pattern Matching