Power Management Agent Throttling for Blade Server Energy
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Solution Overview
Problem
Current computer systems, including blade servers, consume excessive power due to over-provisioning to meet peak demands, leading to inefficiencies and increased operational costs for powering and cooling, with existing technologies failing to effectively manage power consumption and extend the useful life of these systems.
Innovation Solution
A power management agent that predicts future power consumption, determines a power budget threshold, and selectively throttles electronic systems to prevent exceeding this threshold, using a module for communication, power consumption monitoring, system selection, and throttle level determination to enforce a power budget and reduce energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If components are over-provisioned to meet peak demands, then system reliability is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts component provisioning based on actual workload demands. The power management agent continuously monitors power consumption and workload patterns, then adapts the provisioning level of components accordingly. This allows the system to maintain reliability during peak demands while reducing power consumption during lower utilization periods, eliminating the need for static over-provisioning.
Solution Approach 2:
The invention changes the operational parameters of components by adjusting their provisioning levels dynamically. The power management agent modifies parameters such as CPU frequency, memory allocation, and I/O throughput based on real-time conditions. This enables the system to optimize the balance between reliability and power consumption by adjusting parameters rather than maintaining fixed over-provisioned settings.
2Power
If components operate at over-provisioned levels, then peak performance is maintained, but cooling requirements increase
Solution Approach 1:
The power management agent performs preliminary actions by predicting future power consumption patterns and proactively adjusting component provisioning before peak loads occur. This predictive capability allows the system to prepare appropriate cooling resources in advance while avoiding the continuous operation of cooling systems at maximum capacity, thereby reducing overall cooling resource consumption while maintaining peak performance readiness.
Solution Approach 2:
The system implements periodic monitoring and adjustment of component provisioning and cooling resources. The power management agent continuously cycles through monitoring power consumption, analyzing workload patterns, and adjusting provisioning levels. This periodic action enables the system to maintain peak performance only when necessary while reducing cooling requirements during normal operational periods.
3Loss of energy
If power consumption is reduced through throttling, then operational costs are minimized, but system performance may be impacted
Solution Approach 1:
The power management agent implements a feedback mechanism that continuously monitors both power consumption and system performance metrics. Based on this feedback, the agent intelligently adjusts throttling levels to minimize power consumption while maintaining performance within acceptable thresholds. The system learns from historical data and workload patterns to optimize the balance between operational costs and performance, applying throttling only when and where it does not critically impact productivity.
Solution Approach 2:
The invention applies partial throttling actions rather than uniform reduction across all components. The power management agent selectively throttles specific components based on their current utilization and criticality to performance. This partial action approach minimizes the impact on overall system performance while still achieving significant reductions in power consumption and operational costs by focusing throttling on non-critical or underutilized components.
Data Source
AI summary
A power management agent for managing power among electronic systems includes a module for predicting a future power consumption level of the electronic systems, a module for determining a power budget threshold for the electronic systems, and a module for determining whether a predicted future power consumption level will exceed the power budget threshold. The power management agent also includes a module for selecting one or more of the electronic systems to throttle in response to a determination that the predicted future power consumption level will exceed the power budget threshold and a module for selecting a throttle level to be applied to the selected one or more of the electronic systems to substantially prevent the future power consumption level from exceeding the power budget threshold.