An efficient swap algorithm for the lattice Boltzmann method

Mattila, Keijo; Hyväluoma, Jari; Rossi, Tuomo; Aspnäs, Mats; Westerholm, Jan

doi:10.1016/j.cpc.2006.09.005

Cited by 61 publications

(41 citation statements)

References 23 publications

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“…This way of imposing bounce back by omission of the node is called implicit bounce back. This property is shared by other swap methods like the one proposed by Mattila et al [17] and Latt [18] and by the AA-pattern [16].…”

Section: Implicit Bounce Backmentioning

confidence: 74%

“…Such a technique is called in-place streaming and several methods have been proposed in literature. An early example of an in-place streaming algorithm is the swap algorithm of Mattila et al [17] and Latt [18]. The swap algorithm combines the streaming and the collision in a single step, but it does not overwrite the input of the local collision by the output.…”

Section: Implementation Of the Lattice Boltzmann Methodsmentioning

confidence: 99%

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Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware

Geier

Schönherr

2017

Computation

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Abstract:We present and analyze the Esoteric Twist algorithm for the Lattice Boltzmann Method. Esoteric Twist is a thread safe in-place streaming method that combines streaming and collision and requires only a single data set. Compared to other in-place streaming techniques, Esoteric Twist minimizes the memory footprint and the memory traffic when indirect addressing is used. Esoteric Twist is particularly suitable for the implementation of the Lattice Boltzmann Method on Graphic Processing Units.

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Section: Implicit Bounce Backmentioning

confidence: 74%

Section: Implementation Of the Lattice Boltzmann Methodsmentioning

confidence: 99%

Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware

Geier

Schönherr

2017

Computation

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“…LBM is a specific finite-difference discretization of the continuous Boltzmann equation [2] , space (r), velocity (u) and time (t) are all discrete based on the kinetic gas theory. Its main idea is that using the average motion of the particles to describe the macroscopic behavior of the system.…”

Section: Lattice Boltzmann Methodsmentioning

confidence: 99%

“…Shift algorithm [1] applies a data compression technique to reduce the memory consumption of implementations, but it needs additional memory buffer to prevent the overwriting of still useful data. Swap algorithm [2] overlaps two consecutive time steps into one memory block through using an ingenious order to update distribution values, and there is no additional memory allocated in swap algorithm except few temporal variables. Thus in this work swap algorithm is introduced as memory optimization strategy.…”

Section: Introductionmentioning

confidence: 99%

Parallel communication optimization based on least square method for LBM

Cao

Shang

et al. 2011

J. Shanghai Univ.(Engl. Ed.)

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Efficient communication is important to every parallel algorithm. A parallel communication optimization is introduced into lattice Boltzmann method (LBM). It relies on a simplified communication strategy which is implemented by least square method. After testing the improved algorithm on parallel platform, the experimental results show that compared with normal parallel lattice Boltzmann algorithm, it provides better stability, higher performance while maintaining the same accuracy.

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“…Differences between basic algorithms are related to their treatment of this data dependence. We have identified five basic algorithms for the implementation of LBM: the Lagrangian, compressed grid (shift), swap, two-lattice, and twostep algorithm [3][4][5]. Each of these algorithms has its own characteristic features, which are manifested in the efficiency of implementation.…”

Section: Introductionmentioning

confidence: 99%

Comparison of implementations of the lattice-Boltzmann method

Mattila

Hyväluoma

Timonen

et al. 2008

Computers & Mathematics with Applications

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Simplicity of coding is usually an appealing feature of the lattice-Boltzmann method (LBM). Conventional implementations of LBM are often based on the two-lattice or the two-step algorithm, which however suffer from high memory consumption and poor computational performance, respectively. The aim of this work was to identify implementations of LBM that would achieve high computational performance with low memory consumption. Effects of memory addressing schemes were investigated in particular. Data layouts for velocity distribution values were also considered, and they were found to be related to computational performance. A novel bundle data layout was therefore introduced. Addressing schemes and data layouts were implemented for the Lagrangian, compressed-grid (shift), swap, two-lattice, and two-step algorithms. Implementations were compared for a wide range of fluid volume fractions. Simulation results indicated that indirect addressing implementations yield high computational performance. However, they achieved low memory consumption only for very low fluid volume fractions. Semi-direct addressing implementations could also provide high computational performance. The bundle data layout was found to be competitive, sometimes by a wide margin, in all the cases considered.

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An efficient swap algorithm for the lattice Boltzmann method

Cited by 61 publications

References 23 publications

Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware

Esoteric Twist: An Efficient in-Place Streaming Algorithmus for the Lattice Boltzmann Method on Massively Parallel Hardware

Parallel communication optimization based on least square method for LBM

Comparison of implementations of the lattice-Boltzmann method

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