Adaptive Semiconductor Performance Boosting via User Input Monitoring
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Solution Overview
Problem
Existing semiconductor devices face inefficiencies in performance boosting, as current methods often waste battery power by boosting performance unnecessarily, lacking adaptive adjustment based on user input patterns and system usage.
Innovation Solution
A performance boosting method and system for semiconductor devices that monitor user input and system usage, generating user system information to adaptively determine a performance boosting target value, thereby adjusting the operating frequency accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If performance boosting is applied to improve system responsiveness, then system performance is improved, but battery power is wasted when boosting occurs unnecessarily
Solution Approach 1:
The system dynamically adjusts performance boosting based on real-time analysis of user input patterns and system usage states. The processor transitions between different performance states (boosted, normal, low-power) according to detected patterns, making the performance level adaptive rather than static. This resolves the contradiction by applying performance boosting only when dynamically determined to be necessary, rather than continuously or never.
Solution Approach 2:
The system implements feedback mechanisms by monitoring user input patterns, system usage, and performance metrics continuously. This feedback loop allows the system to learn from past behavior and adjust future performance boosting decisions. The feedback enables the system to distinguish between situations requiring performance boosting and those where battery conservation is prioritized, resolving the contradiction between performance and energy waste.
2Productivity
If performance boosting is applied continuously to maintain high system responsiveness, then system performance is maintained, but power consumption increases unnecessarily
Solution Approach 1:
Instead of continuous performance boosting, the system employs periodic monitoring of user input patterns and system usage at specific intervals. Performance boosting is activated periodically based on pattern recognition results rather than continuously. This periodic approach maintains system responsiveness when needed while reducing overall power consumption by allowing the system to operate at lower performance states during normal periods.
Solution Approach 2:
The system changes operational parameters (performance level, clock frequency, power state) based on detected user input patterns and system usage conditions. Rather than maintaining a fixed high-performance state, the processor dynamically adjusts its operating parameters to match actual system needs, reducing power consumption while maintaining responsiveness when patterns indicate user interaction is occurring.
3Duration of action of stationary object
If performance boosting is avoided to conserve battery power, then battery life is extended, but system responsiveness deteriorates when user interaction is needed
Solution Approach 1:
The system performs preliminary analysis of user input patterns to predict when performance boosting will be needed. By detecting patterns indicative of upcoming user interaction (such as specific touch sequences, keyboard patterns, or system usage behaviors), the system can proactively prepare by boosting performance in advance, ensuring responsiveness is ready when needed while avoiding unnecessary continuous boosting that would waste battery life.
Solution Approach 2:
The system uses its own operational data (user input patterns, system usage metrics) to autonomously determine when performance boosting should occur. The processor self-regulates its performance state based on internal monitoring without requiring external control, optimizing the balance between battery life and responsiveness automatically based on actual system conditions and user behavior patterns.
Data Source
AI summary
A performance boosting method of a semiconductor device includes monitoring input of a user and an amount of system usage, generating user system information in response to an event occurring, the user system information including first information and the amount of system usage, the first information regarding input of the user, adaptively determining a performance boosting target value based on the user system information, and boosting an operating frequency according to the performance boosting target value.


