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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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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.

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  3/2018 - 1
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Lattice Boltzmann Method Implementation on Multiple Devices using OpenCL

TEKIC, J. B. See more information about TEKIC, J. B. on SCOPUS See more information about TEKIC, J. B. on IEEExplore See more information about TEKIC, J. B. on Web of Science, TEKIC, P. M. See more information about  TEKIC, P. M. on SCOPUS See more information about  TEKIC, P. M. on SCOPUS See more information about TEKIC, P. M. 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 (1,197 KB) | Citation | Downloads: 491 | Views: 464

Author keywords
Lattice Boltzmann methods, multicore processing, scientific computing, parallel programming, parallel algorithms

References keywords
lattice(21), boltzmann(21), method(11), multi(8), simulations(6), flow(6), flows(5), computational(5), time(4), relaxation(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-08-31
Volume 18, Issue 3, Year 2018, On page(s): 3 - 8
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.03001
Web of Science Accession Number: 000442420900001
SCOPUS ID: 85052088705

Abstract
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Scientific computing community has been in close connection with high performance computing (HPC), which has been privilege of a limited group of scientists. Recently, with rapid development of Graphics Processing Units (GPUs), the parallel processing power of high performance computers has been brought up to every commodity desktop computer, reducing cost of scientific computations. In this paper, we develop a general purpose Lattice Boltzmann code that runs on commodity computer with multiple heterogeneous devices that support OpenCL specification. Different approaches to Lattice Boltzmann code implementations on commodity computer with multiple devices were explored. Simulation results for different code implementations on multiple devices have been compared to each other, to results obtained for single device implementation and with results from the literature. Simulation results for the commodity computer hardware platforms with multiple devices implementation have showed significant speed improvement compared to simulation implemented on single device.


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

[1] W. Shi, W. Shyy, R. Mei, "Finite-difference-based lattice Boltzmann method for inviscid compressible flows," Numerical Heat Transfer, Part B: Fundamentals, vol. 40, no. 1, pp. 1-21, 2001.
[CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 49]


[2] R. Mei, W. Shyy, D. Yu, L.-S. Luo, "Lattice Boltzmann Method for 3-D Flows with Curved Boundary," Journal of Computational Physics, vol. 161, no. 2, pp. 680-699, 2000.
[CrossRef] [Web of Science Times Cited 201] [SCOPUS Times Cited 229]


[3] Z. Guo, T. S. Zhao, "A lattice Boltzmann model for convective heat transfer in porous media," Numerical Heat Transfer, Part B: Fundamentals, vol. 47, no. 2, pp. 157-177, 2005.
[CrossRef] [Web of Science Times Cited 133] [SCOPUS Times Cited 157]


[4] P. M. Tekic, J. B. Rađenovic, N. Lukic, S. S. Popovic, "Lattice Boltzmann simulation of two-sided lid-driven flow in a staggered cavity," International Journal of Computational Fluid Dynamics, vol. 24, no. 9, pp. 383-390, 2010.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 9]


[5] O. Filippova, D. Hanel, "A Novel Lattice BGK Approach for Low Mach Number Combustion," Journal of Computational Physics, vol. 158, no. 2, pp. 139-160, 2000.
[CrossRef] [Web of Science Times Cited 87] [SCOPUS Times Cited 94]


[6] K. Mattila, J. Hyvaluoma, J. Timonen, T. Rossi, "Comparison of implementations of the lattice-Boltzmann method," Computers & Mathematics with Applications, vol. 55, no. 7, pp. 1514-1524, 2008.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 40]


[7] S. Tomov, M. McGuigan, R. Bennett, G. Smith, J. Spiletic, "Benchmarking and implementation of probability-based simulations on programmable graphics cards," Computers & Graphics, vol. 29, no. 1, pp. 71-80, 2005.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 38]


[8] W. Li, X. Wei, A. Kaufman,"Implementing lattice Boltzmann computation on graphics hardware," The Visual Computer, vol. 19, no. 8, pp. 444-456, 2003.
[CrossRef] [Web of Science Times Cited 96] [SCOPUS Times Cited 134]


[9] D. Vidal, R. Roy, F. Bertrand, "A parallel workload balanced and memory efficient lattice-Boltzmann algorithm with single unit BGK relaxation time for laminar Newtonian flows," Computers & Fluids, vol. 39, no. 8, pp. 1411-1423, 2010.
[CrossRef]


[10] J. A. Anderson, C. D. Lorenz, A. Travesset, "General purpose molecular dynamics simulations fully implemented on graphics processing units," Journal of Computational Physics, vol. 227, no. 10, pp. 5342-5359, 2008.
[CrossRef] [Web of Science Times Cited 747] [SCOPUS Times Cited 823]


[11] K. Chen, C. Lin, S. Zhong, L. Guo, "A Parallel SRM Feature Extraction Algorithm for Steganalysis Based on GPU Architecture," Computer Science and Information Systems, vol. 12, no. 4, pp. 1345-1359, 2015.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 1]


[12] P. M. Tekic, J. B. Radjenovic, M. Rackovic, "Implementation of the Lattice Boltzmann Method on Heterogeneous Hardware and Platforms using OpenCL," Advances in Electrical and Computer Engineering, vol. 12, no. 1, pp. 51-56, 2012.
[CrossRef] [Full Text] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[13] C. Obrecht, F. Kuznik, B. Tourancheau, J.-J. Roux, "Multi-GPU implementation of the lattice Boltzmann method," Computers & Mathematics with Applications, vol. 65, no. 2, pp. 252-261, 2013.
[CrossRef] [Web of Science Times Cited 42] [SCOPUS Times Cited 49]


[14] H.-W. Chang, P.-Y. Hong, L.-S. Lin, C.-A. Lin, "Simulations of Three-dimensional Cavity Flows with Multi Relaxation Time Lattice Boltzmann Method and Graphic Processing Units," Procedia Engineering, vol. 61, pp. 94-99, 2013.
[CrossRef] [SCOPUS Times Cited 3]


[15] H.-W. Chang, P.-Y. Hong, L.-S. Lin, C.-A. Lin, "Simulations of flow instability in three dimensional deep cavities with multi relaxation time lattice Boltzmann method on graphic processing units," Computers & Fluids, vol. 88, pp. 866-871, 2013.
[CrossRef] [Web of Science Times Cited 12] [SCOPUS Times Cited 14]


[16] C. Huang, B. Shi, N. He, Z. Chai, "Implementation of Multi-GPU Based Lattice Boltzmann Method for Flow Through Porous Media," Advances in Applied Mathematics and Mechanics, vol. 7, no. 1, pp. 1-12, 2015.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 9]


[17] P.-Y. Hong, L.-M. Huang, L.-S. Lin, C.-A. Lin, "Scalable multi-relaxation-time lattice Boltzmann simulations on multi-GPU cluster," Computers & Fluids, vol. 110, pp. 1-8, 2015.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 11]


[18] W. Xian, A. Takayuki, "Multi-GPU performance of incompressible flow computation by lattice Boltzmann method on GPU cluster," Parallel Computing, vol. 37, no. 9, pp. 521-535, 2011.
[CrossRef] [Web of Science Times Cited 54] [SCOPUS Times Cited 72]


[19] B. Massimo, F. Massimiliano, M. Simone, S. Sauro, K. Efthimios, "A flexible high-performance Lattice Boltzmann GPU code for the simulations of fluid flows in complex geometries,"Concurrency and Computation: Practice and Experience, vol. 22, no. 1, pp. 1-14, 2010.
[CrossRef]


[20] E. Calore, S. F. Schifano, R. Tripiccione, "A Portable OpenCL Lattice Boltzmann Code for Multi- and Many-core Processor Architectures," Procedia Computer Science, vol. 29, pp. 40-49, 2014.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 10]


[21] P. L. Bhatnagar, E. P. Gross, M. Krook, "A Model for Collision Processes in Gases. I. Small Amplitude Processes in Charged and Neutral One-Component Systems," Physical Review, vol. 94, no. 3, pp. 511-525, 1954.
[CrossRef] [SCOPUS Times Cited 4815]


[22] X. He, L. Luo, "Theory of the lattice Boltzmann method: From the Boltzmann equation to the lattice Boltzmann equation," Physical Review, vol. 56, no. 6, pp. 6811-6817, 1997.
[CrossRef] [Web of Science Times Cited 901] [SCOPUS Times Cited 1025]


[23] D. V. Patil, K. N. Lakshmisha, B. Rogg, "Lattice Boltzmann simulation of lid-driven flow in deep cavities," Computers & Fluids, vol. 35, no. 10, pp. 1116-1125, 2006.
[CrossRef] [Web of Science Times Cited 47] [SCOPUS Times Cited 52]


[24] S. Hou, Q. Zou,S. Chen, G. Doolen, A. C. Cogley, "Simulation of Cavity Flow by the Lattice Boltzmann Method," Journal of Computational Physics, vol. 118, no. 2, pp. 329-347, 1995.
[CrossRef] [Web of Science Times Cited 438] [SCOPUS Times Cited 519]




References Weight

Web of Science® Citations for all references: 2,910 TCR
SCOPUS® Citations for all references: 8,155 TCR

Web of Science® Average Citations per reference: 116 ACR
SCOPUS® Average Citations per reference: 326 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 2019-01-15 23:22 in 177 seconds.




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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.

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