Parallel Bitonic Sorting Components for Data Sequence Efficiency
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Solution Overview
Problem
Bitonic sort algorithms require multiple rounds of traversal for sorting tasks, leading to increased execution time and reduced sorting efficiency.
Innovation Solution
A data processing method that involves acquiring a data sorting request, invoking C data bitonic sorting components, initiating B data bitonic sorting tasks, operating the components in parallel to obtain sorting subresults, and combining these subresults to achieve a data sorting result.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bitonic sort algorithm is used for data sorting, then the sorting can be implemented with definite execution time and is suitable for hardware implementation, but multiple rounds of traversal are required which increases execution time and reduces sorting efficiency
Solution Approach 1:
The patent divides the data sequence into multiple data subsequences and assigns different bitonic sorting components to process each subsequence independently. This segmentation allows parallel execution of sorting operations, reducing the total execution time while maintaining the reliable definite execution time characteristic of bitonic sort. Each component processes a subset of data, and the results are combined to produce the final sorted output.
2Manufacturing precision
If multiple rounds of traversal are performed during bitonic sort execution, then complete sorting can be achieved, but the execution time increases and sorting efficiency decreases
Solution Approach 1:
The patent introduces a parallel dimension by deploying multiple bitonic sorting components that operate simultaneously on different data subsequences. Instead of performing multiple sequential rounds of traversal, the system executes multiple sorting operations in parallel across different components, achieving the same sorting completeness with reduced total execution time. The combination of results from parallel components maintains sorting precision while eliminating time loss.
Data Source
AI summary
A data processing method includes: acquiring a data sorting request for a data sequence to be sorted, and invoking C data bitonic sorting components in response to the data sorting request, C being a positive integer greater than 1; initiating B data bitonic sorting tasks according to the data sequence and the C data bitonic sorting components, B being a positive integer greater than 1, the B data bitonic sorting tasks being respectively associated with different data subsequences of B data subsequences, and the B data subsequences being generated based on the to-be-sorted data sequence; operating the C data bitonic sorting components in parallel according to the B data bitonic sorting tasks to obtain B data sorting subresults; and combining the B data sorting subresults based on the C data bitonic sorting components to obtain a data sorting result for the data sequence.