2006 · 240 citations · 13 references
EngineeringComputer EngineeringComputer SystemsDesign AutomationHardware-software Co-designLow-power DesignCompute Resource ManagementPerformance ModelingPower ManagementPower-aware DesignResource SchedulingThermal ManagementDensityEnergy-aware OptimizationEnergy-efficient ArchitecturePower Management TechniquesResource Allocation For Energy EfficiencySystem-level Power OptimizationThermal-aware DesignThermal-aware Energy Management
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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Web search for a planet: the google cluster architecture
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Energy conservation in heterogeneous server clusters
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