A parallel method for computing convex hulls based on multi-core architecture

By employing classification-based computation and multi-directional array point decomposition methods under a multi-core architecture, the integration problem in convex hull computation is solved, improving computational efficiency and scalability while reducing complexity and power consumption.

CN115994283BActive Publication Date: 2026-05-01ZHEJIANG GONGSHANG UNIVERSITY
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Patent Information

Application Number
CN202211450314.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-11-19
Publication Date
2026-05-01
Estimated Expiration
2042-11-19

AI Technical Summary

Technical Problem

In multi-core architectures, existing technologies struggle to effectively address the integration problem in convex hull computation, making it impossible to simply decompose the divide-and-conquer strategy and leaving the solution perplexing.

Method used

By re-entering the convex hull point after the non-empty point set is implanted into the JDSS(S) interval and then being transferred out of the serial interval after being identified as unqualified by the JDSS(S) interval, a classification calculation method is adopted, which is combined with multi-directional array points and conjugate functions for decomposition, and the sub-problems are solved in parallel using a divide-and-conquer strategy.

Benefits of technology

It achieves an efficient solution to the integration problem of convex hull computing under a multi-core architecture, improving computing efficiency and scalability while reducing complexity and power consumption.

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Abstract

This invention relates to the field of geometric computation technology, specifically to a parallel method for computing convex hulls based on a multi-core architecture, comprising the following steps: a. During the algorithm process, arbitrary convex hull points are sorted into a point array, and combined with the identification algorithm window to form the first elimination of non-convex hull points, and the three-dimensional extreme points formed along the horizontal and vertical directions are found. During the process of identifying whether the algorithm points are completely convex hull points, incomplete convex hull points in the algorithm points are simultaneously marked to form a convex hull point array NCP(S), and the complete convex hull edge chain in the algorithm points is NCE(S); b. The convex hull point array NCP(S) and the convex hull edge chain NCE(S) need to be backed up to form a multi-directional array point; This invention re-enters the convex hull point array after the non-empty point set is implanted into the JDSS(S) interval and is identified as unqualified after being implanted into the JDSS(D) interval, thereby exiting the serial interval, thereby classifying and calculating algorithms with large combination problems, and achieving the purpose of solving the problem.
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