Optimal Computing System Configuration via Root Mean Square Normalization
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Solution Overview
Problem
Current systems for configuring and optimizing computing systems, such as converged infrastructures, lack consistency due to subjective balancing of functional requirements with resource constraints, leading to varying recommendations from design engineers for the same specifications.
Innovation Solution
A method that accesses functional and resource constraint information, converts it into hardware and resource models, generates utilization models, and identifies a best-fit configuration based on determined values, ensuring objective optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If design engineers manually balance functional requirements with resource constraints, then flexibility in handling complex specifications is improved, but consistency and objectivity deteriorate
Solution Approach 1:
The patent replaces the manual mechanical process of balancing requirements with an automated computer-based system that uses algorithms and mathematical models (including root mean square normalization) to objectively evaluate configurations, eliminating human subjectivity while maintaining the ability to handle complex specifications
Solution Approach 2:
The system transforms the subjective balancing process into an objective parameter-based evaluation by converting functional requirements and resource constraints into quantifiable models, where configurations are ranked using calculated scores based on normalized parameter comparisons
2Manufacturing precision
If detailed hardware specifications are defined for all viable configurations, then functional requirements satisfaction is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex configuration problem into distinct components: functional requirements models, resource constraint models, and an objective function. Each component is modeled separately and then integrated through systematic evaluation, making the overall complex system manageable through modular analysis
Data Source
AI summary
A system, method, and computer program product for determining an optimal configuration for a computing system. For example, a method may include accessing functional requirements and resource constraint information. Functional requirements are converted into hardware requirements and functional models are generated, each of which satisfies the hardware requirements. Functional models are converted to functional utilization models, and functional utilization model values are generated for the functional utilization models. The method also may include defining a resource model for each of the functional models and converting the resource models to resource utilization models. A resource utilization model value is generated for each of the resource utilization models. A set of viable models is identified based on the values for the functional utilization models and the resource utilization models, and then a best fit model is identified based on the determined functional model value and the determined resource constraint model value.