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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Vydáno v:	2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Ročník 5; s. 555 - 561
Hlavní autoři:	Potebnia, Artem, Pogorilyy, Sergiy
Médium:	Konferenční příspěvek Journal Article
Jazyk:	angličtina
Vydáno:	Polish Information Processing Society (PIPS) 01.09.2015 Polish Information Processing Society
Témata:	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
On-line přístup:	Získat plný text
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Popis
Shrnutí:	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