Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: May 2018
Next issue: Aug 2018
Avg review time: 108 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


TRAFFIC STATS

1,993,760 unique visits
539,162 downloads
Since November 1, 2009



Robots online now
BINGbot


SJR SCImago RANK

SCImago Journal & Country Rank


SEARCH ENGINES

aece.ro - Google Pagerank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 18 (2018)
 
     »   Issue 2 / 2018
 
     »   Issue 1 / 2018
 
 
 Volume 17 (2017)
 
     »   Issue 4 / 2017
 
     »   Issue 3 / 2017
 
     »   Issue 2 / 2017
 
     »   Issue 1 / 2017
 
 
 Volume 16 (2016)
 
     »   Issue 4 / 2016
 
     »   Issue 3 / 2016
 
     »   Issue 2 / 2016
 
     »   Issue 1 / 2016
 
 
 Volume 15 (2015)
 
     »   Issue 4 / 2015
 
     »   Issue 3 / 2015
 
     »   Issue 2 / 2015
 
     »   Issue 1 / 2015
 
 
  View all issues  








LATEST NEWS

2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

Read More »


    
 

  1/2012 - 9

Implementation of the Lattice Boltzmann Method on Heterogeneous Hardware and Platforms using OpenCL

TEKIC, P. M. See more information about TEKIC, P. M. on SCOPUS See more information about TEKIC, P. M. on IEEExplore See more information about TEKIC, P. M. on Web of Science, RADJENOVIC, J. B. See more information about  RADJENOVIC, J. B. on SCOPUS See more information about  RADJENOVIC, J. B. on SCOPUS See more information about RADJENOVIC, J. B. on Web of Science, RACKOVIC, M. See more information about RACKOVIC, M. on SCOPUS See more information about RACKOVIC, M. on SCOPUS See more information about RACKOVIC, M. 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 (662 KB) | Citation | Downloads: 911 | Views: 3,193

Author keywords
GPU, Java, lattice Boltzmann method, many-core, OpenC

References keywords
lattice(17), boltzmann(15), performance(5), fluid(5), flow(5), simulation(4), parallel(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2012-02-28
Volume 12, Issue 1, Year 2012, On page(s): 51 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.01009
Web of Science Accession Number: 000301075000009
SCOPUS ID: 84860735612

Abstract
Quick view
Full text preview
The Lattice Boltzmann method (LBM) has become an alternative method for computational fluid dynamics with a wide range of applications. Besides its numerical stability and accuracy, one of the major advantages of LBM is its relatively easy parallelization and, hence, it is especially well fitted to many-core hardware as graphics processing units (GPU). The majority of work concerning LBM implementation on GPU's has used the CUDA programming model, supported exclusively by NVIDIA. Recently, the open standard for parallel programming of heterogeneous systems (OpenCL) has been introduced. OpenCL standard matures and is supported on processors from most vendors. In this paper, we make use of the OpenCL framework for the lattice Boltzmann method simulation, using hardware accelerators - AMD ATI Radeon GPU, AMD Dual-Core CPU and NVIDIA GeForce GPU's. Application has been developed using a combination of Java and OpenCL programming languages. Java bindings for OpenCL have been utilized. This approach offers the benefits of hardware and operating system independence, as well as speeding up of lattice Boltzmann algorithm. It has been showed that the developed lattice Boltzmann source code can be executed without modification on all of the used hardware accelerators. Performance results have been presented and compared for the hardware accelerators that have been utilized.


References | Cited By  «-- Click to see who has cited this paper

[1] G. Khanna and J. McKennon, "Numerical modeling of gravitational wave sources accelerated by OpenCL," Computer Physics Communications, vol. 181 pp. 1605-1611, 2010.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 22]


[2] M. J. Harvey and G. D. Fabritiis, "Swan: A tool for porting CUDA programs to OpenCL," Computer Physics Communications.

[3] S. Succi, The Lattice Boltzman Equation for Fluid Dynamics and Beyond. Oxford: Oxford University Press, 2001.

[4] D. Yu, R. Mei, L.-S. Luo, and W. Shyy, "Viscous low computations with the method of lattice Boltzmann equation," Progress in Aerospace Sciences, vol. 39, pp. 329-367, 2003.
[CrossRef] [Web of Science Times Cited 505] [SCOPUS Times Cited 604]


[5] L.-S. Luo, "The lattice-gas and lattice Boltzmann methods: Past, present, and future," in Proc Int Conf Appl Comput Fluid Dyn, Beijing, 2000, pp. 52-83.

[6] M. C. Sukop and D. T. J. Thorne, Lattice Boltzmann Modeling: An Introduction for Geoscientists and Engineers. Berlin: Springer, 2007.

[7] S. Williams, J. Carter, L. Oliker, J. Shalf, and K. A. Yelick, "Lattice Boltzmann simulation optimization on leading multicore platforms," in IEEE International Symposium on Parallel and Distributed Processing, 2008, pp. 1-14.
[CrossRef] [SCOPUS Times Cited 49]


[8] T. Pohl, et al., "Performance Evaluation of Parallel Large-Scale Lattice Boltzmann Applications on Three Supercomputing Architectures," presented at the Proceedings of the 2004 ACM/IEEE conference on Supercomputing, 2004.
[CrossRef] [SCOPUS Times Cited 29]


[9] G. Wellein, T. Zeiser, G. Hager, and S. Donath, "On the single processor performance of simple lattice Boltzmann kernels," Computers & Fluids, vol. 35, pp. 910-919.
[CrossRef] [Web of Science Times Cited 115] [SCOPUS Times Cited 135]


[10] D. Vidal, R. Roy, and F. Bertrand, "A parallel workload balanced and memory efficient lattice-Boltzmann algorithm," Computers & Fluids, vol. 39, pp. 1411-1423, 2010.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 9]


[11] M. Bernaschi, M. Fatica, S. Melchionna, S. Succi, and E. Kaxiras, "A flexible high-performance Lattice Boltzmann GPU code for the simulations of fluid flows in complex geometries," Concurr. Comput. : Pract. Exper., vol. 22, pp. 1-14, 2010.
[CrossRef] [Web of Science Times Cited 51] [SCOPUS Times Cited 69]


[12] K. R. Tubbs and F. T. C. Tsai, "GPU accelerated lattice Boltzmann model for shallow water flow and mass transport," International Journal for Numerical Methods in Engineering, vol. 86, pp. 316-334, 2011.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 20]


[13] W. Li, X. Wei, and A. Kaufman, "Implementing Lattice Boltzmann Computation on Graphics Hardware," Visual Computer, vol. 19, pp. 444-456, 2003.

[14] J. Tolke and M. Krafczyk, "TeraFLOP computing on a desktop PC with GPUs for 3D CFD," International Journal of Computational Fluid Dynamics, vol. 22, pp. 443-456, 2008.
[CrossRef] [Web of Science Times Cited 150] [SCOPUS Times Cited 180]


[15] F. Kuznik, C. Obrecht, G. Rusaouen, and J.-J. Roux, "LBM based flow simulation using GPU computing processor," Computers & Mathematics with Applications, vol. 59, pp. 2380-2392, 2010.
[CrossRef] [Web of Science Times Cited 81] [SCOPUS Times Cited 94]


[16] J. Habich, T. Zeiser, G. Hager, and G. Wellein, "Performance analysis and optimization strategies for a D3Q19 lattice Boltzmann kernel on nVIDIA GPUs using CUDA," Advances in Engineering Software, vol. 42, pp. 266-272, 2011.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 19]


[17] C. Obrecht, F. Kuznik, B. Tourancheau, and J.-J. Roux, "A new approach to the lattice Boltzmann method for graphics processing units," Computers & Mathematics with Applications, vol. In Press, Corrected Proof.

[18] W. Xian and A. Takayuki, "Multi-GPU performance of incompressible flow computation by lattice Boltzmann method on GPU cluster," Parallel Computing, vol. In Press, Corrected Proof.

[19] JOCL Library, [Online] Available: Temporary on-line reference link removed - see the PDF document

[20] P. M. Tekic, J. B. Radenovic, N. L. Lukic, and S. S. Popovic, "Lattice Boltzmann simulation of two-sided lid-driven flow in a staggered cavity," International Journal of Computational Fluid Dynamics, vol. 24, pp. 383-390, 2010.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 8]


[21] D. V. Patil, K. N. Lakshmisha, and B. Rogg, "Lattice Boltzmann simulation of lid-driven flow in deep cavities," Computers & Fluids, vol. 35, pp. 1116-1125, 2006.
[CrossRef] [Web of Science Times Cited 44] [SCOPUS Times Cited 50]


References Weight

Web of Science® Citations for all references: 1,008 TCR
SCOPUS® Citations for all references: 1,288 TCR

Web of Science® Average Citations per reference: 48 ACR
SCOPUS® Average Citations per reference: 61 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-07-22 18:16 in 99 seconds.




Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2018
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: