Multi-Coring Computing Module Execution with Asynchronous Output
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Solution Overview
Problem
Large entities face inefficiencies due to network bottlenecks and latency caused by computationally expensive functions that require extensive computational resources, leading to prolonged execution times and inefficiencies in processing large amounts of data.
Innovation Solution
A system determines whether a computing module is suitable for multi-coring, dedicating specific computing cores to execute functions asynchronously, maintaining output order in a list data structure and converting it to a data frame structure upon completion, thereby optimizing resource usage and reducing bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If computationally expensive functions are executed using conventional single-core processing, then computational resources are preserved for other tasks, but execution time increases significantly and network latency occurs
Solution Approach 1:
The patent segments the computationally expensive function into multiple independent tasks that can be executed in parallel across multiple computing cores. Each core handles a portion of the computation independently, allowing simultaneous processing and reducing overall execution time while maintaining system productivity.
Solution Approach 2:
The patent transitions from single-dimensional sequential execution to multi-dimensional parallel execution by utilizing multiple computing cores simultaneously. This dimensional shift from one-core processing to many-core processing enables concurrent task execution, dramatically reducing execution time without sacrificing processing throughput.
2Productivity
If multiple functions are executed concurrently on shared computing resources, then processing throughput increases, but network bottlenecks and latency occur
Solution Approach 1:
The patent segments computing resources into dedicated cores for specific functions, preventing resource contention and network bottlenecks. By assigning specific cores to specific computationally expensive functions, the system maintains high processing throughput while ensuring reliable network performance as dedicated cores do not compete for shared resources.
Solution Approach 2:
The patent applies local quality by dedicating specific computing cores to specific functions based on their computational requirements. This localized resource allocation ensures that network-sensitive functions receive dedicated processing power, maintaining network reliability while the overall system achieves high throughput through parallel execution of multiple functions on different cores.
3Speed
If computing cores are dedicated to execute single functions, then execution speed increases, but device complexity increases
Solution Approach 1:
The patent segments the computing system into dedicated cores for specific functions, which simplifies the management complexity by creating clear, isolated execution contexts. Each dedicated core executes its assigned function without interference from other tasks, maintaining high execution speed while the segmentation actually reduces complexity compared to managing shared resources with context switching and resource contention.
Data Source
AI summary
Described herein is a system for executing a computing module. Described herein is a system for executing a computing module. The system may determine whether a function of a computing module is suitable to be executed using multi-coring. The system identifies one or more available computing cores and executes the function on the one or more available computing cores. The one or more available computing cores can be dedicated to execute the function until the execution of the function is complete. The one or more available computing cores execute the tasks of the function asynchronously. The system receives output data from the function asynchronously in a list data structure. The system can maintain a desired order of the output data in the list data structure.