Processor Turbo Mode Duration Control via Thermal Feedback
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Solution Overview
Problem
Current power management techniques for multicore processors are limited in optimizing turbo mode operations due to reliance on short-term characterization and thermal throttling, leading to suboptimal performance and energy efficiency, especially in varying ambient temperatures and user behavior.
Innovation Solution
Implementing dynamic field-based self-optimized turbo mode control that allows the processor to learn and adapt within a system, incorporating user input and real-time measurements to optimize power and performance limits based on cooling capabilities and user needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the processor operates at higher power levels to increase performance, then processing speed and computational capability are improved, but thermal management becomes more difficult and energy consumption increases
Solution Approach 1:
The patent implements dynamic turbo mode operation where the processor can switch between different power and performance states based on real-time thermal conditions and workload requirements. The system dynamically adjusts operational parameters including turbo mode duration, power consumption levels, and performance states to optimize the balance between processing speed and thermal management, rather than using fixed static configurations
Solution Approach 2:
The system changes multiple operational parameters simultaneously including turbo mode time duration, power consumption levels, and performance states. By adjusting these parameters dynamically based on thermal feedback and workload characteristics, the system can operate at higher performance levels when thermal conditions permit while maintaining adequate thermal management
2Device complexity
If the processor uses fixed pre-defined turbo mode settings, then power management is simplified, but performance optimization is limited and cannot adapt to varying user behavior and environmental conditions
Solution Approach 1:
The processor implements self-optimizing capabilities through on-board intelligence that automatically monitors thermal conditions, workload patterns, and performance requirements. The system autonomously adjusts turbo mode settings and power management parameters without requiring external intervention or complex configuration, enabling adaptive performance optimization while maintaining manageable system complexity
Solution Approach 2:
The system incorporates feedback mechanisms that continuously monitor thermal conditions, power consumption, and performance metrics. This feedback is used to dynamically adjust turbo mode operation and power management settings, enabling the processor to adapt to varying environmental conditions and user behavior patterns while optimizing performance
3Productivity
If the processor extends turbo mode duration to improve performance, then computational throughput increases, but thermal load accumulates and energy consumption rises
Solution Approach 1:
The system employs periodic turbo mode operation where high-performance bursts are interspersed with lower-power intervals. By controlling the duration and frequency of turbo mode activation based on thermal conditions and workload characteristics, the system achieves improved computational throughput while managing energy consumption through rhythmic on-off cycles rather than continuous high-power operation
Solution Approach 2:
The processor dynamically adjusts turbo mode duration and power levels in real-time based on thermal feedback and performance requirements. This dynamic control enables the system to extend turbo operation when beneficial for throughput while automatically reducing power consumption when thermal or energy constraints are approached
4Productivity
If the processor implements adaptive learning to optimize power management, then performance and energy efficiency are improved, but system complexity and measurement requirements increase
Solution Approach 1:
The processor implements self-learning capabilities that automatically monitor and adapt to usage patterns, thermal characteristics, and performance requirements over time. Through on-board intelligence and autonomous decision-making, the system optimizes power management and turbo mode operation without requiring external configuration or complex control infrastructure, improving energy efficiency while maintaining practical system complexity
Data Source
AI summary
In one embodiment, a processor includes at least one core, at least one thermal sensor, and a power controller including a first logic to dynamically update a time duration for which the at least one core is enabled to be in a turbo mode. Other embodiments are described and claimed.


