Intelligent Computing Resource Allocation System
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Solution Overview
Problem
Computing systems face limitations in prioritizing tasks effectively due to insufficient resources and human bias in subjective decision-making, leading to inefficient load distribution and scheduling issues when multiple tasks compete for shared computing resources.
Innovation Solution
A system that dynamically prioritizes the allocation of computing resources using a reward score calculated based on utility and resource cost factors, allowing for intelligent retraining of models by determining a prioritized order for resource allocation and automatically adjusting schedules in response to changes in resource availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If computing resources are allocated based on human subjective prioritization, then ease of operation is improved, but productivity deteriorates due to inefficient load distribution and scheduling issues
Solution Approach 1:
The system enables automated self-service scheduling where the computing system autonomously prioritizes and allocates resources based on quantitative task characteristics. The scheduler automatically evaluates tasks using predefined criteria (computational requirements, deadlines, resource availability) and makes scheduling decisions without human intervention, resolving the contradiction by replacing subjective human operation with objective automated decision-making that improves productivity while maintaining ease of use through automation.
2Productivity
If computing resources are allocated to all submitted tasks simultaneously, then productivity is improved, but loss of energy increases due to insufficient resources and system overload
Solution Approach 1:
The system implements partial action by selectively allocating computing resources only to tasks that can be effectively executed with available resources. The scheduler evaluates task priorities, resource requirements, and current system capacity to determine which tasks receive resource allocation. This prevents system overload and energy waste on tasks that cannot be completed, while still maintaining high productivity by ensuring resources are directed to the most valuable tasks.
Solution Approach 2:
The scheduling system dynamically adjusts resource allocation based on real-time conditions including current resource availability, task urgency, and system load. The scheduler continuously monitors system state and reprioritizes tasks as conditions change, allowing the system to adapt resource distribution to maximize productivity while avoiding energy loss from overallocation. This dynamic approach enables the system to respond to changing demands without wasting energy on unsustainable task execution.
3Ease of operation
If computing resources are allocated based on first-come-first-served, then ease of operation is improved, but loss of time increases due to inefficient prioritization of important tasks
Solution Approach 1:
The system changes the prioritization parameter from temporal (first-come-first-served) to value-based (task importance, computational requirements, deadlines). The scheduler assigns priority levels to tasks based on multiple parameters including resource requirements, urgency, and strategic importance. This parameter change allows the system to maintain ease of operation through automated rule-based scheduling while dramatically reducing time loss by ensuring critical tasks are executed before less important ones, regardless of submission order.
Data Source
AI summary
Some embodiments herein disclose intelligent priority evaluators configured to perform a method that prioritizes tasks submitted by various users, even if the tasks are similarly classified. The scheduling system can collect, calculate, and use various criteria to determine a reward score in order to prioritize one task over another, such as for dynamic scheduling purposes. This can be performed in addition to or as a replacement for receiving user designations of priority.