Power Budget Allocation Engine for Computing Systems
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Solution Overview
Problem
Existing system-wide power and thermal management in computing systems often inefficiently allocate resources, leading to suboptimal performance and potential component damage due to inadequate consideration of individual component needs and dependencies.
Innovation Solution
A power budget allocation engine dynamically adjusts power allocations between components based on their specific needs, preferences, and system-wide conditions, using a software policy manager to prioritize performance and manage thermal budgets effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a system-wide power management device allocates power budget to components, then overall power consumption is controlled, but individual component performance may be suboptimal due to inability to utilize additional power resources efficiently
Solution Approach 1:
The patent divides the system-wide power management into component-level autonomous decision-making. Each component (CPU, GPU, etc.) independently monitors its own power usage and performance needs, then requests additional power budget from the system manager. This segmentation allows each component to optimize its own performance while the system manager ensures overall power constraints are met, resolving the contradiction between efficient power usage and component performance.
Solution Approach 2:
The patent implements local quality by allowing each component to have its own power management characteristics and decision-making capabilities. Instead of a uniform system-wide approach, each component can independently evaluate whether additional power would be useful based on its specific operational state, dependencies on other components, and current performance needs. This local autonomy enables more efficient power utilization at the component level while maintaining system-wide power control.
2Productivity
If additional power is allocated to a component, then that component can process more information, but it may not provide a valuable result if other components cannot keep up
Solution Approach 1:
The patent implements feedback mechanisms where each component monitors not only its own power consumption but also the operational state of other components it depends on. Before requesting additional power, a component evaluates whether other components can keep up with the increased processing demand. This feedback loop prevents situations where one component receives additional power but cannot produce useful results due to bottlenecks elsewhere in the system, thereby avoiding wasted energy and ensuring that power allocation translates to actual productive output.
3Adaptability or versatility
If a system-wide device determines power allocation, then centralized control is achieved, but the complexity of evaluating component-specific needs and dependencies increases
Solution Approach 1:
The patent applies self-service by enabling components to autonomously evaluate their own power needs and make informed requests for additional power budget. Each component independently monitors its operational state, assesses its dependencies on other components, and determines whether additional power would be beneficial. This self-service approach dramatically reduces the complexity of the system-wide power management device, as it no longer needs to directly evaluate component-specific details but rather processes simple requests from components that have already performed the complex evaluation themselves.
Data Source
AI summary
According to some embodiments, a power budget allocation engine of a multi-component computer system may receive a power budget allocation adjustment request signal from a first component. Based on the received budget allocation adjustment request signal (and, in some embodiments, a component preference), the power budget allocation engine may determine whether to adjust a power budget allocation signal provided to the first component.