Coordinated Optimization: Dynamic Energy Allocation in Enterprise Workload
Controlling how much power server machines draw has become increasingly important in recent years. Observing how variations in a workload affect the power drawn by different server components provides data critical for analysis and for building models relating quality of service expectations to power consumption. This paper describes a process of observation, modeling, and course corrections that is successful in achieving autonomic power control in an Intel Xeon E5-2600 server machine meeting varying response time and throughput demands during the execution of a database query workload.
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