Dynamic Power Budgeting for Computer Systems
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Solution Overview
Problem
Current power budgeting in computers is wasteful as it often exceeds actual maximum power requirements, leading to inefficiencies and potential failures due to insufficient power, with manufacturers assigning higher nominal power to avoid blame.
Innovation Solution
Implementing a dynamic power budgeting system using power monitors associated with each component, which gather and analyze power consumption data to adjust power allocation based on actual usage, issuing warnings and allowing for automatic or user-driven adjustments to prevent exceeding maximum power limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If power supply is selected to handle maximum power requirements including margin for upgrades, then system reliability is improved, but cost and heat removal requirements increase
Solution Approach 1:
The patent implements dynamic power budgeting that adjusts power allocation in real-time based on actual component power consumption rather than static maximum ratings. Power monitors continuously measure actual power usage and the system dynamically reallocates power budgets among components, allowing the power supply to operate closer to actual needs rather than worst-case scenarios, thereby reducing heat removal requirements while maintaining system reliability.
Solution Approach 2:
The system changes the parameter of power allocation from fixed nominal values to dynamic values based on monitored actual consumption. By continuously adjusting power budgets based on measured power usage and predicted future needs, the system optimizes the balance between reliability and energy efficiency, preventing both power shortages and excessive heat generation.
2Reliability
If nominal maximum power is assigned higher than actual requirements, then manufacturer liability is reduced, but power usage efficiency deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where power monitors continuously measure actual power consumption and feed this information back to the power budgeting system. This real-time feedback allows the system to base power allocation on actual usage patterns rather than conservative nominal ratings, improving power usage efficiency while still maintaining adequate headroom for reliability through predictive analysis and dynamic adjustment.
Solution Approach 2:
The system performs preliminary power budgeting based on actual measured consumption patterns before making allocation decisions. By analyzing historical power usage data and predicting future needs, the system proactively configures optimal power distribution, avoiding both the waste of excessive nominal allocations and the risk of insufficient power for actual requirements.
3Stability of the object's composition
If power allocation is based on static maximum ratings, then system stability is improved, but adaptability to actual usage patterns deteriorates
Solution Approach 1:
The patent transitions from static power allocation based on fixed maximum ratings to dynamic power budgeting that adapts to actual usage patterns. The system continuously monitors power consumption and adjusts allocations in real-time, maintaining system stability through controlled dynamic adjustment while achieving adaptability to varying workload demands and component requirements.
Solution Approach 2:
The power monitoring and budgeting system enables components to effectively self-report their power needs through continuous measurement and analysis. The system autonomously adjusts power allocation based on actual consumption patterns without requiring manual intervention or conservative over-provisioning, achieving both stability and adaptability through intelligent self-management.
Data Source
AI summary
A computer system uses power-consumption monitors for each of plural sets of devices. A power budget arbiter determines whether a collective power-consumption criterion is met at least in part as a function of said power-consumption data.