ComputingComputer EngineeringHigh-performance ComputingCloud ArchitectureCloud InfrastructureVirtualizationCompute Resource ManagementData Center VirtualizationEnergy MeteringPerformance ModelingPower ManagementWorkload PlacementApplication-specific Power EstimationCloud Data CentersCloud Resource MeteringEvaluation BenchmarksModeling PowerPower Management TechniquesResource MeteringVirtualized Data Centers
The increasing heterogeneity between applications in emerging virtualized data centers like clouds introduce significant challenges in estimating the power drawn by the data center. In this work, we presentWattApp: an application-aware power meter for shared data centers that addresses this challenge. In order to deal with heterogeneous applications, WattApp introduces application parameters (e.g, throughput) in the power modeling framework. WattApp is based on a carefully designed set of experiments on a mix of diverse applications: power benchmarks, web-transaction workloads, HPC workloads and I/O-intensive workloads. Given a set of N applications and M server types, WattApp runs in O(N) time, uses O(NxM) calibration runs, and predicts the power drawn by any arbitrary placement within 5%of the real power for the applications studied.
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