Parallel lattice boltzmann flow simulation on emerging multi-core platforms

Liu Peng; Ken Ichi Nomura; Takehiro Oyakawa; Rajiv K. Kalia; Aiichiro Nakano; Priya Vashishta

doi:10.1007/978-3-540-85451-7_81

Parallel lattice boltzmann flow simulation on emerging multi-core platforms

Liu Peng
, Ken Ichi Nomura
, Takehiro Oyakawa
, Rajiv K. Kalia
, Aiichiro Nakano
, Priya Vashishta

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Scopus citations

Abstract

A parallel Lattice Boltzmann Method (pLBM), which is based on hierarchical spatial decomposition, is designed to perform large-scale flow simulations. The algorithm uses critical section-free, dual representation in order to expose maximal concurrency and data locality. Performances of emerging multi-core platforms-PlayStation3 (Cell Broadband Engine) and Compute Unified Device Architecture (CUDA)-are tested using the pLBM, which is implemented with multi-thread and message-passing programming. The results show that pLBM achieves good performance improvement, 11.02 for Cell over a traditional Xeon cluster and 8.76 for CUDA graphics processing unit (GPU) over a Sempron central processing unit (CPU). The results provide some insights into application design on future many-core platforms. © 2008 Springer-Verlag Berlin Heidelberg.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	763-777
Number of pages	15
Volume	5168 LNCS
DOIs	https://doi.org/10.1007/978-3-540-85451-7_81
State	Published - Sep 22 2008
Externally published	Yes

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Peng, L., Nomura, K. I., Oyakawa, T., Kalia, R. K., Nakano, A., & Vashishta, P. (2008). Parallel lattice boltzmann flow simulation on emerging multi-core platforms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5168 LNCS, pp. 763-777) https://doi.org/10.1007/978-3-540-85451-7_81

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title = "Parallel lattice boltzmann flow simulation on emerging multi-core platforms",

abstract = "A parallel Lattice Boltzmann Method (pLBM), which is based on hierarchical spatial decomposition, is designed to perform large-scale flow simulations. The algorithm uses critical section-free, dual representation in order to expose maximal concurrency and data locality. Performances of emerging multi-core platforms-PlayStation3 (Cell Broadband Engine) and Compute Unified Device Architecture (CUDA)-are tested using the pLBM, which is implemented with multi-thread and message-passing programming. The results show that pLBM achieves good performance improvement, 11.02 for Cell over a traditional Xeon cluster and 8.76 for CUDA graphics processing unit (GPU) over a Sempron central processing unit (CPU). The results provide some insights into application design on future many-core platforms. {\textcopyright} 2008 Springer-Verlag Berlin Heidelberg.",

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Parallel lattice boltzmann flow simulation on emerging multi-core platforms. / Peng, Liu; Nomura, Ken Ichi; Oyakawa, Takehiro et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5168 LNCS 2008. p. 763-777.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Parallel lattice boltzmann flow simulation on emerging multi-core platforms

AU - Peng, Liu

AU - Nomura, Ken Ichi

AU - Oyakawa, Takehiro

AU - Kalia, Rajiv K.

AU - Nakano, Aiichiro

AU - Vashishta, Priya

PY - 2008/9/22

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AB - A parallel Lattice Boltzmann Method (pLBM), which is based on hierarchical spatial decomposition, is designed to perform large-scale flow simulations. The algorithm uses critical section-free, dual representation in order to expose maximal concurrency and data locality. Performances of emerging multi-core platforms-PlayStation3 (Cell Broadband Engine) and Compute Unified Device Architecture (CUDA)-are tested using the pLBM, which is implemented with multi-thread and message-passing programming. The results show that pLBM achieves good performance improvement, 11.02 for Cell over a traditional Xeon cluster and 8.76 for CUDA graphics processing unit (GPU) over a Sempron central processing unit (CPU). The results provide some insights into application design on future many-core platforms. © 2008 Springer-Verlag Berlin Heidelberg.

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EP - 777

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -

Parallel lattice boltzmann flow simulation on emerging multi-core platforms

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