Parallel Processing Task Segmentation for Serial Bottleneck Resolution
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Solution Overview
Problem
Existing data processing systems fail to optimize processing time when both parallel and serial processing are involved, as serial processing tends to become a bottleneck despite increased computer resources.
Innovation Solution
A data processing system that divides parallel processing tasks into subtasks and assigns them to multiple computers, ensuring that subtasks are completed before serial processing tasks, thereby optimizing the overall processing time by scheduling large serial processing tasks concurrently with other tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If parallel processing is used to process record sets, then processing speed is improved, but serial processing becomes a bottleneck that limits overall processing time optimization
Solution Approach 1:
The patent segments the parallel processing tasks into multiple sub-tasks based on the size of record sets. Each sub-task is assigned to a different computer, allowing simultaneous execution. This segmentation enables the system to overcome the bottleneck of serial processing by distributing work across multiple computers while maintaining the sequential dependency structure of the original tasks.
Solution Approach 2:
The patent introduces a new dimension of task execution by allowing sub-tasks to be performed in parallel across multiple computers while maintaining the original serial processing sequence. This dimensional change enables concurrent execution without violating the sequential dependency requirement, thereby reducing overall processing time.
2Loss of time
If record sets are divided into sub-tasks for parallel processing, then processing time is reduced, but task assignment complexity increases
Solution Approach 1:
The patent applies local quality by assigning sub-tasks to computers based on the specific characteristics of each record set and the processing requirements. Each computer receives a tailored set of sub-tasks appropriate to its capabilities and the data distribution, optimizing processing efficiency without requiring complex centralized control.
Solution Approach 2:
The system performs self-service by automatically dividing record sets into sub-tasks and assigning them to available computers based on predefined criteria. This self-service mechanism eliminates the need for complex manual task assignment while maintaining optimal processing time, as the system autonomously manages the parallel processing workflow.
Data Source
AI summary
Disclosed are a data processing system, etc., whereby total processing time of a data process including a parallel process and a serial process is optimized. This data processing system comprises: a task segmenting means for receiving a plurality of tasks which execute, upon a record set which is a set of a plurality of records, a data process which includes parallel processes which a plurality of computers are capable of executing in parallel and serial processes which are post-processes of the parallel processes and is executed by one computer, and, for a parallel process which is the pre-process of a serial process, among the serial processes which are included in the task, which is envisioned as requiring more time to process than another serial process, by subdividing the record set which is to be processed in the parallel process, segmenting the parallel process into a plurality of sub-tasks; and an assignment means for assigning the plurality of sub-tasks to the plurality of computers, such that the plurality of sub-tasks are executed prior to a task other than the task which includes the parallel processes being executed.