Innovative GPU accelerated algorithm for fast minimum convex hulls computation

Innovative algorithm for forming graph minimum convex hulls using the GPU is proposed. High speed and linear complexity of this method are achieved by distribution of the graph's vertices into separate units and their filtering. The key factor for improving the performance of innovative algorit...

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Bibliographic Details
Published in:2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Vol. 5; pp. 555 - 561
Main Authors: Potebnia, Artem, Pogorilyy, Sergiy
Format: Conference Proceeding Journal Article
Language:English
Published: Polish Information Processing Society (PIPS) 01.09.2015
Polish Information Processing Society
Subjects:
Acceleration
Approximation algorithms
Clustering algorithms
CPU+GPU hybrid system
CUDA
GPGPU technology
Graph
Graphics processing units
High-performance computing
Minimum convex hull
Streaming media
Time complexity
ISSN:2300-5963
Online Access:Get full text
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Summary:Innovative algorithm for forming graph minimum convex hulls using the GPU is proposed. High speed and linear complexity of this method are achieved by distribution of the graph's vertices into separate units and their filtering. The key factor for improving the performance of innovative algorithm is the massively-parallel implementation of local hulls formation using video accelerators. A computational process is controlled by means of auxiliary matrices. A number of experimental studies of the algorithm have been carried out, and its suitability for application in the hull processing for large-scale problems has been demonstrated. The speed of the new method is 10 - 20 times higher compared to using functions of the professional mathematical package Wolfram Mathematica.
ISSN:2300-5963
DOI:10.15439/2015F305