Dynamic Power Budgeting in Data Processing Systems
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Solution Overview
Problem
As computer systems face increasing power consumption from individual components, designing systems to handle continuous worst-case workloads while maintaining high performance, compactness, and battery efficiency becomes challenging, especially in portable devices where power budgets are tight.
Innovation Solution
A data processing system dynamically budgets power usage by estimating power consumption requirements based on operating signals and actual usage, allowing for throttle settings to be adjusted in components like CPUs and GPUs to manage power within constraints, ensuring performance levels are maintained without exceeding power limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system is designed to handle continuous worst-case workload, then reliability is improved, but power consumption increases and performance is limited
Solution Approach 1:
The patent implements dynamic power management by continuously monitoring actual power consumption and adjusting component throttle settings in real-time. The system transitions from static worst-case design to dynamic adaptation, where power allocation changes based on actual workload conditions. This allows the system to maintain reliability during high-demand periods while reducing power consumption during lower-demand periods.
Solution Approach 2:
The system changes operational parameters by adjusting throttle settings of components based on monitored power consumption levels. When power consumption approaches budget limits, the system dynamically modifies performance parameters (such as CPU frequency, GPU clock speed) to stay within power constraints while maintaining system reliability through adaptive control.
2Power
If component operating power increases, then computing power is improved, but power budget is exceeded
Solution Approach 1:
The patent employs feedback mechanisms by continuously monitoring actual power consumption of components and using this information to adjust throttle settings. The monitoring system provides real-time feedback on power usage, and the control system responds by adjusting component performance levels to ensure the total power consumption remains within the allocated power budget while maximizing computing power utilization.
Solution Approach 2:
The system allows components to operate at higher power levels temporarily when actual consumption is below the budget, effectively using partial power allocation dynamically. When power budget headroom exists, components can exceed their baseline power allocation to deliver peak computing performance, and when the budget is approached, power allocation is reduced accordingly.
3Use of energy by moving object
If throttle settings are adjusted to manage power, then power consumption is reduced, but performance may be limited
Solution Approach 1:
The patent implements dynamic throttle adjustment where performance limitations are applied adaptively rather than statically. The system continuously evaluates actual power consumption and temporarily relaxes throttle settings when power budget allows, enabling performance to scale dynamically with available power headroom while ensuring power consumption constraints are never violated.
Data Source
AI summary
Methods and apparatuses for dynamically budgeting power usage in a data processing system. In one aspect, a data processing system, includes: one or more components including a first component; and a computing element, such as a microprocessor or a microcontroller, coupled to the first component to obtain one or more operating signals from the first component and to determine, based at least in part on the one or more operating signals, an estimate of a power consumption requirement of the one or more components for operating under the current condition. In one example, one or more sensors are used to determine information on actual power usage for a past period of time. A performance level setting of a second component, such as a CPU, a GPU, or a bus, is determined using the estimate and the information on the actual power usage, such as the operating voltage and frequency.