Publication | Closed Access
Ensemble-level Power Management for Dense Blade Servers
240
Citations
13
References
2006
Year
Unknown Venue
Cluster ComputingBlade Enclosure LevelEngineeringEnergy EfficiencyPower Optimization (Eda)Computer ArchitectureSystems EngineeringParallel ComputingPower-aware DesignPower-aware SoftwarePower-aware ComputingData Center SystemComputer EngineeringComputer ScienceHeat DensityConcurrent Resource UsageDense Blade ServersSmart GridEnergy ManagementEdge ComputingCloud ComputingParallel ProgrammingPower-efficient Computing
One of the key challenges for high-density servers (e.g., blades) is the increased costs in addressing the power and heat density associated with compaction. Prior approaches have mainly focused on reducing the heat generated at the level of an individual server. In contrast, this work proposes power efficiencies at a larger scale by leveraging statistical properties of concurrent resource usage across a collection of systems ("ensemble"). Specifically, we discuss an implementation of this approach at the blade enclosure level to monitor and manage the power across the individual blades in a chassis. Our approach requires low-cost hardware modifications and relatively simple software support. We evaluate our architecture through both prototyping and simulation. For workloads representing 132 servers from nine different enterprise deployments, we show significant power budget reductions at performances comparable to conventional systems.
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