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JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Feb 2021
Next issue: May 2021
Avg review time: 56 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2020-Jun-29
Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

2020-Jun-11
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2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

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  2/2015 - 5

 HIGHLY CITED PAPER 

CudaPre3D: An Alternative Preprocessing Algorithm for Accelerating 3D Convex Hull Computation on the GPU

MEI, G. See more information about MEI, G. on SCOPUS See more information about MEI, G. on IEEExplore See more information about MEI, G. on Web of Science, XU, N. See more information about XU, N. on SCOPUS See more information about XU, N. on SCOPUS See more information about XU, N. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,043 KB) | Citation | Downloads: 371 | Views: 2,822

Author keywords
computational geometry, computer aided engineering, multicore processing, parallel algorithms, parallel programming

References keywords
convex(20), hull(14), hulls(5), graphics(5), algorithm(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2015-05-31
Volume 15, Issue 2, Year 2015, On page(s): 35 - 44
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.02005
Web of Science Accession Number: 000356808900005
SCOPUS ID: 84979726246

Abstract
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In the calculating of convex hulls for point sets, a preprocessing procedure that is to filter the input points by discarding non-extreme points is commonly used to improve the computational efficiency. We previously proposed a quite straightforward preprocessing approach for accelerating 2D convex hull computation on the GPU. In this paper, we extend that algorithm to being used in 3D cases. The basic ideas behind these two preprocessing algorithms are similar: first, several groups of extreme points are found according to the original set of input points and several rotated versions of the input set; then, a convex polyhedron is created using the found extreme points; and finally those interior points locating inside the formed convex polyhedron are discarded. Experimental results show that: when employing the proposed preprocessing algorithm, it achieves the speedups of about 4x on average and 5x to 6x in the best cases over the cases where the proposed approach is not used. In addition, more than 95 percent of the input points can be discarded in most experimental tests.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 6
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Cited-By CrossRef

[1] CudaCHPre2D: A straightforward preprocessing approach for accelerating 2D convex hull computations on the GPU, Qin, Jiayu, Mei, Gang, Cuomo, Salvatore, Guo, Sixu, Li, Yixuan, Concurrency and Computation: Practice and Experience, ISSN 1532-0626, Issue 10, Volume 32, 2020.
Digital Object Identifier: 10.1002/cpe.5229
[CrossRef]

[2] A General-Purpose Graphics Processing Unit (GPGPU)-Accelerated Robotic Controller Using a Low Power Mobile Platform, Rizvi, Syed, Cabodi, Gianpiero, Patti, Denis, Gulzar, Muhammad, Journal of Low Power Electronics and Applications, ISSN 2079-9268, Issue 2, Volume 7, 2017.
Digital Object Identifier: 10.3390/jlpea7020010
[CrossRef]

[3] A hardware-efficient parallel architecture for real-time blob analysis based on run-length code, Li, Bingjie, Zhang, Cunguang, Li, Bo, Jiang, Hongxu, Xu, Qizhi, Journal of Real-Time Image Processing, ISSN 1861-8200, Issue 3, Volume 15, 2018.
Digital Object Identifier: 10.1007/s11554-017-0709-0
[CrossRef]

[4] CudaChain: an alternative algorithm for finding 2D convex hulls on the GPU, Mei, Gang, SpringerPlus, ISSN 2193-1801, Issue 1, Volume 5, 2016.
Digital Object Identifier: 10.1186/s40064-016-2284-4
[CrossRef]

[5] RUN: rational ubiquitous navigation, a model for automated navigation and searching in virtual environments, Raees, Muhammad, Ullah, Sehat, Virtual Reality, ISSN 1359-4338, 2020.
Digital Object Identifier: 10.1007/s10055-020-00468-0
[CrossRef]

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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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