Performance evaluation of a two-dimensional lattice Boltzmann solver using CUDA and PGAS UPC based parallelisation

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2017-07-31

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Association for Computing Machinery (ACM)

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Article

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0098-3500

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Máté Szőke, Tamás István Józsa, Ádám Koleszár, Irene Moulitsas and László Könözsy. Performance evaluation of a two-dimensional lattice Boltzmann solver using CUDA and PGAS UPC based parallelisation. ACM Transactions on Mathematical Software (TOMS), Volume 44 Issue 1, July 2017, article number 8

Abstract

The Unified Parallel C (UPC) language from the Partitioned Global Address Space (PGAS) family unifies the advantages of shared and local memory spaces and offers a relatively straightforward code parallelisation with the Central Processing Unit (CPU). In contrast, the Computer Unified Device Architecture (CUDA) development kit gives a tool to make use of the Graphics Processing Unit (GPU). We provide a detailed comparison between these novel techniques through the parallelisation of a two-dimensional lattice Boltzmann method based fluid flow solver. Our comparison between the CUDA and UPC parallelisation takes into account the required conceptual effort, the performance gain, and the limitations of the approaches from the application oriented developers’ point of view. We demonstrated that UPC led to competitive efficiency with the local memory implementation. However, the performance of the shared memory code fell behind our expectations, and we concluded that the investigated UPC compilers could not efficiently treat the shared memory space. The CUDA implementation proved to be more complex compared to the UPC approach mainly because of the complicated memory structure of the graphics card which also makes GPUs suitable for the parallelisation of the lattice Boltzmann method.

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Partitioned global address space, unified parallel C, nvidia, compute unified device architecture, computational fluid dynamics, lattice Boltzmann method

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Attribution-NonCommercial 4.0 International
©ACM 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. Please refer to any applicable publisher terms of use. The definitive version was published in ACM Transactions on Mathematical Software (TOMS), Volume 44 Issue 1, July 2017, http://doi.acm.org/10.1145/3085590

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