Resource Feasibility Modeling for Supply-Constrained Capacity
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Solution Overview
Problem
Modern computing systems face challenges in effectively managing supply-constrained resources like accelerator chips, where availability is unpredictable, leading to difficulties in understanding feasibility of resource capacity under varying scenarios.
Innovation Solution
A method and system for modeling demand feasibility using a solver engine and capacity data calculator to determine partitioning and feasibility of supply-constrained resources based on availability and historical data, providing answers to user queries about resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If supply-constrained resources are pooled for shared use by multiple users, then resource utilization is maximized, but availability becomes unpredictable
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing capacity data for supply-constrained resources under various scenarios before users make requests. The capacity data calculator service computes availability information in advance, considering different time periods, locations, and demand conditions, so that when a user queries feasibility, the solver engine can quickly retrieve and analyze pre-computed data rather than calculating from scratch.
Solution Approach 2:
The patent introduces an intermediary feasibility assessment system consisting of the capacity data calculator service and solver engine. This intermediary layer sits between the pooled resources and multiple users, mediating the complexity of resource availability by translating raw capacity data into user-friendly feasibility assessments. The intermediary handles the unpredictability internally while presenting deterministic feasibility results to users.
2Loss of information
If users want to understand feasibility of obtaining desired capacity under different scenarios, then user confidence increases, but system complexity increases
Solution Approach 1:
The system segments the complex feasibility assessment task into distinct functional components: the capacity data calculator service that gathers and processes raw availability data, the solver engine that performs feasibility analysis, and the interface that presents results to users. Each component handles a specific aspect of the problem, making the overall complex system manageable through modular organization.
Solution Approach 2:
The system creates simplified copies or representations of the complex resource availability problem. Instead of presenting users with raw, complex capacity data and requiring them to understand underlying constraints, the solver engine generates simplified feasibility assessments that copy the essential information needed for decision-making while filtering out unnecessary complexity.
Data Source
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AI summary
The present disclosure provides methods and systems for managing user queries concerning fulfillment of requests to use a supply constrained resource. A method may involve receiving a user query specifying a requested supply constrained resource, the user query including one or more parameters, providing the user query to a solver engine, accessing availability information indicating an availability of the supply constrained resource, determining a partitioning of the supply constrained resource based on the availability information, providing the determined partitioning of the supply constrained resource to the solver engine, determining, by the solver engine, a feasibility of a user request to use the supply constrained resource having the one or more parameters of the user query, and outputting, from the solver engine, the determined feasibility of the user request.