Metrics, Models and Methodologies for Energy-Proportional Computing

Cluster, Cloud and Grid Computing(2014)

Cited 5|Views9
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Abstract
Improving non-peak power efficiency has the potential to significantly enhance the efficiency of a data center and allows us to host more resources under a given power budget. In this paper, we use RAPL interfaces to analyze and model the performance (both throughput and response time) of SPECweb benchmark under subsystem-level power limits. We show that performance under a subsystem-level power limits can be modeled using simple and well-studied non-linear models. We then leverage a load prediction model and an optimization framework to create a runtime system for power management of enterprise application. Our work shows that effective subsystem-level power capping improves the energy proportionality of the server.
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Key words
benchmark testing,business data processing,computer centres,power aware computing,RAPL interfaces,SPECweb benchmark,data center,energy-proportional computing,enterprise application,load prediction model,nonlinear models,nonpeak power efficiency improvement,optimization framework,performance analysis,power budget,power management,response time,running average power limit interfaces,runtime system,subsystem-level power capping,subsystem-level power limits,throughput,Energy-proportional Computing,Enterprise Workloads,Green Computing,RAPL
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