Processor Power Management via Adaptive Operating Points
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Solution Overview
Problem
Current power management techniques for processors rely on predefined worst-case operating constraints, which may lead to unnecessary power consumption when actual operating conditions differ from these constraints, as they do not adaptively adjust operating parameters based on real-time measurements.
Innovation Solution
The method involves defining operating points based on target operating constraints that are not necessarily worst-case, allowing for adaptive switching of processor operational profiles by adjusting core voltage and clock rate based on actual junction temperature measurements, thereby optimizing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If predefined worst-case operating constraints are used for power management, then processor reliability is ensured under all conditions, but power consumption increases unnecessarily when actual conditions are better than worst-case
Solution Approach 1:
The patent applies dynamics by transitioning from static worst-case operating constraints to dynamic operating points that adapt in real-time based on actual processor conditions. The system continuously monitors junction temperature and adjusts operating parameters (voltage, frequency) dynamically, allowing the processor to operate at optimal points rather than being constrained by fixed worst-case values. This resolves the contradiction by maintaining reliability through continuous adaptation while reducing unnecessary power consumption when conditions permit.
Solution Approach 2:
The patent implements feedback mechanisms by monitoring actual processor junction temperature and using this information to adjust operating points. The system measures real-time temperature conditions and feeds this information back to the power management logic, which then selects appropriate operating points from a set of predefined characteristics. This feedback loop ensures reliability by responding to actual conditions while avoiding the excessive power consumption associated with static worst-case constraints.
2Use of energy by moving object
If operating parameters are adjusted to limit power consumption, then energy efficiency improves, but processor performance may be compromised
Solution Approach 1:
The patent applies parameter changes by defining multiple operating points with different combinations of voltage, frequency, and power consumption characteristics. Instead of uniformly reducing parameters to limit power consumption, the system selects from a set of predefined operating points that offer different trade-offs between performance and power usage. This allows the processor to maintain high performance when needed while achieving energy efficiency when lower performance is acceptable, resolving the contradiction through selective parameter adjustment.
Solution Approach 2:
The system dynamically selects operating points based on real-time conditions, allowing it to optimize the balance between performance and power consumption. When thermal conditions and workload permit, the processor can operate at high-performance points; when power savings are prioritized or thermal conditions require it, the system transitions to lower-power operating points. This dynamic adaptation resolves the contradiction by allowing both high performance and energy efficiency at different times based on actual needs.
3Use of energy by moving object
If adaptive switching of operational profiles is implemented, then power consumption is optimized for actual conditions, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the continuous operating space into discrete operating points with predefined characteristics. Instead of implementing complex real-time optimization algorithms, the system segments the operating space into a finite set of characterized points, each with known voltage, frequency, and power consumption properties. The power management logic then selects from this segmented set based on monitored conditions, achieving power optimization while limiting complexity through the use of predefined discrete options rather than continuous adjustment.
Data Source
AI summary
Techniques are generally described related to management of power consumption for a processor. One example method may include identifying a target operating constraint and a first operating parameter; determining a second operating parameter based on the target operating constraint and the first operating parameter; estimating an actual operating constraint; comparing the target operating constraint and the actual operating constraint; and setting up the first operating parameter and the second operating parameter of the processor based on a comparison of the target operating constraint and the actual operating constraint, wherein the target operating constraint is not a worst-case operating constraint. Other examples of methods, systems, and computer programs related to managing power consumption for a processor are also contemplated.