An optimized D2Q37 Lattice Boltzmann code on GP-GPUs

被引：19

作者：

Biferale, Luca ^{[1
,2
]}

Mantovani, Filippo ^{[3
]}

Pivanti, Marcello ^{[4
,5
]}

Pozzati, Fabio ^{[6
]}

Sbragaglia, Mauro ^{[1
,2
]}

Scagliarini, Andrea ^{[7
]}

Schifano, Sebastiano Fabio ^{[4
,5
]}

Toschi, Federico ^{[8
,9
]}

Tripiccione, Raffaele ^{[5
,10
,11
]}

机构：

[1] Univ Roma Tor Vergata, I-00173 Rome, Italy

[2] Ist Nazl Fis Nucl, I-00173 Rome, Italy

[3] Deutsch Elektronen Synchrotron DESY, D-15738 Zeuthen, Germany

[4] Univ Ferrara, I-44124 Ferrara, Italy

[5] Ist Nazl Fis Nucl, I-44124 Ferrara, Italy

[6] Fdn Bruno Kessler Trento, I-38122 Trento, Italy

[7] Univ Barcelona, Barcelona 08007, Spain

[8] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands

[9] CNR, IAC, I-00185 Rome, Italy

[10] Univ Ferrara, Ist Nazl Fis Nucl, I-44124 Ferrara, Italy

[11] CMCS, I-44124 Ferrara, Italy

来源：

COMPUTERS & FLUIDS | 2013年 / 80卷

关键词：

Computational fluid-dynamics; Lattice Boltzmann methods; GP-GPU computing;

D O I：

10.1016/j.compfluid.2012.06.003

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We describe the implementation of a thermal compressible Lattice Boltzmann algorithm on an NVIDIA Tesla C2050 system based on the Fermi GP-GPU. We consider two different versions, including and not including reactive effects. We describe the overall organization of the algorithm and give details on its implementations. Efficiency ranges from 25% to 31% of the double precision peak performance of the GP-GPU. We compare our results with a different implementation of the same algorithm, developed and optimized for many-core Intel Westmere CPUs. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：55 / 62

页数：8

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