Information Handling System Profiles for Adaptive Workload Configuration
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Solution Overview
Problem
Existing information handling systems lack an efficient method to dynamically configure their operation based on varying user needs and application requirements, leading to suboptimal performance in terms of power consumption, acoustic noise, and temperature management.
Innovation Solution
A computer-implemented method that iteratively evaluates and ranks multiple profiles based on input data, selecting the best configuration for an information handling system by prioritizing variants such as performance per watt, power improvement, fan improvement, and acoustic noise reduction, ultimately configuring the system to optimize performance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the information handling system uses a fixed configuration, then the system structure is simple and easy to manage, but the system cannot adapt to varying user needs and application requirements, leading to suboptimal performance
Solution Approach 1:
The patent implements dynamic configuration by allowing the information handling system to automatically adjust operational parameters based on detected application types and workload characteristics. The system transitions from a static fixed configuration to a dynamic adaptive configuration that changes in real-time based on system state and user needs.
Solution Approach 2:
The system performs self-configuration by automatically detecting the running application, analyzing workload characteristics, and selecting appropriate operational profiles without requiring manual user intervention. This self-service approach resolves the contradiction by making the system adaptable while keeping the user experience simple.
2Use of energy by moving object
If the system operates without dynamic configuration, then power consumption management is inefficient, but implementing dynamic configuration requires complex evaluation and ranking mechanisms
Solution Approach 1:
The patent pre-defines multiple operational profiles with predetermined configurations optimized for different application types and workload characteristics. By preparing these configurations in advance, the system can quickly select and apply the most appropriate profile without performing complex real-time optimization calculations, thus improving power efficiency while limiting computational complexity.
Solution Approach 2:
The system improves power consumption efficiency by changing operational parameters (such as processor frequency, memory allocation, and peripheral device activation) based on detected workload characteristics. These parameter changes are implemented by selecting from pre-defined profiles rather than performing complex real-time optimization.
3Temperature
If the system lacks dynamic configuration capabilities, then temperature management is suboptimal, but implementing profile-based configuration requires iterative evaluation of multiple variants
Solution Approach 1:
The patent pre-configures multiple operational profiles with different thermal management strategies tailored to various application types. By preparing these profiles in advance with predetermined processor throttling, fan control, and power management settings, the system can effectively manage temperature without performing complex real-time thermal optimization.
4Power
If the information handling system does not dynamically configure operation, then performance per watt is suboptimal, but implementing dynamic configuration requires gathering and analyzing multiple input data parameters
Solution Approach 1:
The system automatically gathers operational data from sensors and system monitors, detects the running application type, analyzes workload characteristics, and selects the most appropriate operational profile without requiring manual user input or complex external analysis tools. This self-service approach improves performance per watt while keeping the system simple to use.
Data Source
AI summary
Embodiments may include a system and method for configuring operation of an information handling system based on a plurality of variants. Embodiments may determine the statistical operations for the variants, define priorities (for example less noise vs. better performance) and use iterative approximation of each variant in relation to all variants to select a profile and then configure operation of the information handling system based on the selected profile.


