2017
DOI: 10.1155/2017/3409647
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MPI to Coarray Fortran: Experiences with a CFD Solver for Unstructured Meshes

Abstract: High-resolution numerical methods and unstructured meshes are required in many applications of Computational Fluid Dynamics (CFD). These methods are quite computationally expensive and hence benefit from being parallelized. Message Passing Interface (MPI) has been utilized traditionally as a parallelization strategy. However, the inherent complexity of MPI contributes further to the existing complexity of the CFD scientific codes. The Partitioned Global Address Space (PGAS) parallelization paradigm was introdu… Show more

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Cited by 4 publications
(3 citation statements)
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“…It has been noted in the literature that different hardware platforms, coupled with different software environments and compiler vendors, can result in performance variation [29].…”
Section: Hardware and Softwarementioning
confidence: 99%
“…It has been noted in the literature that different hardware platforms, coupled with different software environments and compiler vendors, can result in performance variation [29].…”
Section: Hardware and Softwarementioning
confidence: 99%
“…We therefore recommend the support of parallel evaluations of the process models on multiple cores (e.g. with Co-array Fortran and/or MPI [39,40,41])…”
Section: Accepted Manuscriptmentioning
confidence: 99%
“…Although these features have seen relatively slow implementation by the compiler vendors, applications that use native parallel features are becoming more common (e.g., Garain, Balsara, and Reid 2015;Mozdzynski, Hamrud, and Wedi 2015;Shterenlikht, Margetts, and Cebamanos 2018;Curcic 2019;Diaz et al 2021). Today, Fortran remains the dominant language used on top High Performance Computing (HPC) systems, with applications to weather and climate (Powers et al 2017;Skamarock, Ong, and Klemp 2021), computational chemistry ( Čertík, Pask, and Vackář 2013;Apra et al 2020), computational fluid dynamics (Sharma and Moulitsas 2017), life science (Aguilar et al 2018;Vandenplas et al 2020), and economics (Harrison and Pearson 1996;Fehr and Kindermann 2018).…”
Section: Introductionmentioning
confidence: 99%