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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Stammdatenmanagement zwischen Handel und Konsumgüterindustrie : Referenzarchitektur für die überbetriebliche Datensynchronisation /

Schemm, Jan Werner. Unknown Date (has links)
Sankt Gallen, Universiẗat, Diss., 2008.
2

Application interference analysis: Towards energy-efficient workload management on heterogeneous micro-server architectures

Hähnel, Markus, Arega, Frehiwot Melak, Dargie, Waltenegus, Khasanov, Robert, Castrillo, Jeronimo 11 May 2023 (has links)
The ever increasing demand for Internet traffic, storage and processing requires an ever increasing amount of hardware resources. In addition to this, infrastructure providers over-provision system architectures to serve users at peak times without performance delays. Over-provisioning leads to underutilization and thus to unnecessary power consumption. Therefore, there is a need for workload management strategies to map and schedule different services simultaneously in an energy-efficient manner without compromising performance, specially for heterogeneous micro-server architectures. This requires statistical models of how services interfere with each other, thereby affecting both performance and energy consumption. Indeed, the performance-energy behavior when mixing workloads is not well understood. This paper presents an interference analysis for heterogeneous workloads (i.e., CPU- and memory-intensive) on a big.LITTLE MPSoC architecture. We employ state-of-the-art tools to generate multiple single-application mappings and characterize the interference among two different services. We observed a performance degradation factor between 1.1 and 2.5. For some configurations, executing on different clusters resulted in reduced energy consumption with no performance penalty. This kind of detailed analysis give us first insights towards more general models for future workload management systems.

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