Self-Tuning Hardware Resource Configuration Engine
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Solution Overview
Problem
Current computer systems lack an efficient mechanism for self-tuning hardware resources to optimize performance based on real-time monitoring and dynamic adjustment of hardware resource utilization, leading to sub-optimal operation.
Innovation Solution
A system comprising a processor, hardware resource, operating system, metric monitoring unit, and configuration engine that determines and enforces primary and secondary sub-ranges for hardware resource metrics, allowing for the execution of optimization routines to bring resource utilization within optimal ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hardware resources are statically configured without self-tuning capability, then system simplicity is maintained, but performance optimization is lost
Solution Approach 1:
The hardware resource is equipped with self-tuning capability through integrated monitoring and configuration components that automatically adjust operational parameters without external intervention, enabling the system to optimize its own performance dynamically
Solution Approach 2:
A monitoring component continuously tracks hardware resource performance metrics and feeds this information to a configuration component, which then adjusts operational parameters based on the feedback to maintain optimal performance levels
2Productivity
If manual tuning of hardware resources is performed, then performance can be optimized, but time consumption and operational complexity increase
Solution Approach 1:
The system performs automatic self-tuning through integrated monitoring and configuration components that continuously optimize hardware resource parameters without requiring manual intervention, eliminating time loss associated with manual tuning
Solution Approach 2:
The monitoring component operates continuously to track hardware resource performance, and the configuration component continuously adjusts parameters based on monitored data, ensuring uninterrupted optimization without manual intervention
3Adaptability or versatility
If hardware resources operate without dynamic adjustment capability, then system stability is maintained, but adaptability to varying workloads is reduced
Solution Approach 1:
The hardware resource operational parameters are made dynamically adjustable through the self-tuning mechanism, allowing the system to adapt to varying workloads while maintaining stability through controlled, automated adjustments based on real-time monitoring
Data Source
AI summary
A system for self-tuning hardware resources includes a processor, a hardware resource, an operating system (OS), a metric monitoring unit (MMU), and a configuration engine (CE). The OS determines: the hardware resource; a metric for monitoring the hardware resource; a hardware resource management policy for the hardware resource; and a primary and secondary sub-ranges for the metric. The OS sends a hardware resource management policy directive to the CE. The MMU monitors the hardware resource to obtain data for the metric. The CE receives the hardware resource management policy directive, determines the primary and secondary sub-ranges from the hardware resource management policy directive, obtains data for the metric from the MMU. When data is outside the primary sub-range and inside the secondary sub-range, the CE determines and executes a hardware resource optimization routine to bring hardware resource utilization into compliance with the primary sub-range.