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Implementation of the Lattice Boltzmann Method on Heterogeneous Hardware and Platforms using OpenCLTEKIC, P. M. , RADJENOVIC, J. B. , RACKOVIC, M. |
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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
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. |
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[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 83] Web of Science® Citations for all references: 1,521 TCR SCOPUS® Citations for all references: 1,901 TCR Web of Science® Average Citations per reference: 72 ACR SCOPUS® Average Citations per reference: 91 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 2024-11-18 17:21 in 93 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. |
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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