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• W2034787422 abstract "Enterprises rely on decision support systems to influence critical business choices. At the same time, IT-related power costs are growing and are a key concern for enterprise executives. Yet, there is little work to date characterizing the power use of decision support systems. Towards this end, we present the first holistic measurements and analysis of an audit-class system running the TPC-H decision support benchmark at the 300GB scale. We first provide a breakdown of the system's power use into its core hardware components. We then explore its power-performance tradeoffs. This investigation shows that there is ample room to improve its energy use without sacrificing much performance. Moreover, the most energy-efficient configuration depends on the workload. These results suggest that, going forward, database software has an important role to play in optimizing for energy use." @default.
• W2034787422 created "2016-06-24" @default.
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• W2034787422 date "2009-08-19" @default.
• W2034787422 modified "2023-09-27" @default.
• W2034787422 title "Tracking the power in an enterprise decision support system" @default.
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• W2034787422 doi "https://doi.org/10.1145/1594233.1594295" @default.
• W2034787422 hasPublicationYear "2009" @default.
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