Processor Core Selection Algorithm for Power and Thermal Optimization
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Solution Overview
Problem
The increasing demand for performance in thin systems, such as smartphones and tablets, leads to higher processor core counts, which result in increased power consumption and higher temperatures, reducing battery life and user experience, while most applications still utilize only two processor cores intensively, making additional cores less effective.
Innovation Solution
The method involves determining the state of a computing device and calculating ratios of current leakage among processor cores to select the most suitable core combinations based on boundary values, optimizing power consumption and performance by selecting preferred processor cores and their activation sequence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If more processor cores are added to improve performance, then processing capability is improved, but power consumption and temperature increase
Solution Approach 1:
The system dynamically changes operational parameters by selecting different processor core combinations based on current device state (temperature, power conditions, workload). Instead of using all cores continuously, the system adjusts which specific cores are active, changing the operational state to optimize the balance between performance and power consumption.
Solution Approach 2:
The processor core selection is made dynamic rather than static. The system continuously monitors device state and adjusts the active core configuration in real-time, allowing the processing system to adapt its behavior based on current conditions, thereby improving efficiency without sacrificing necessary performance.
2Productivity
If more processor cores are added to improve performance, then processing capability is improved, but temperature increases
Solution Approach 1:
The system changes operational parameters by selecting different core combinations based on temperature conditions. When temperature thresholds are approached, the system transitions to using fewer cores or different core configurations, thereby controlling thermal output while maintaining adequate processing capability.
Solution Approach 2:
The core selection mechanism dynamically responds to temperature conditions, allowing the system to adapt its thermal profile in real-time. This dynamic adjustment prevents thermal runaway while maintaining processing efficiency within safe operating parameters.
3Device complexity
If processor cores are selected without optimization, then device complexity is reduced, but power consumption and temperature increase
Solution Approach 1:
The system changes the selection criteria based on device state parameters. By establishing boundary values and inequalities related to power consumption and temperature, the system dynamically determines which core combinations are acceptable under current conditions, optimizing energy efficiency without requiring complex manual configuration.
Data Source
AI summary
Aspects include computing devices, systems, and methods for selecting preferred processor core combinations for a state of a computing device. In an aspect, a state of a computing device containing the multi-core processor may be determined. A number of current leakage ratios may be determined by comparing current leakages of the processor cores to current leakages of the other processor cores. The ratios may be compared to boundaries for the state of the computing device in respective inequalities. A processor core associated with a number of boundaries may be selected in response to determining that the respective inequalities are true. The boundaries may be associated with a set of processor cores deemed preferred for an associated state of the computing device. The processor core present in the set of processor cores for each boundary of a true inequality may be the selected processor core.