Zynq cluster for CFD parametric survey

Naru Sugimoto, Takaaki Miyajima, Ryotaro Sakai, Yasunori Osana, Naoyuki Fujita, Hideharu Amano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fast Aerodynamics Routines (FaSTAR) is a state of the art Computational Fluid Dynamics (CFD) software package to enable high precise analysis. Due to its complicated data structure from unstructured grid, the acceleration with GPU or massively parallel machines is not efficient. Although a hardware accelerator on an FPGA is a hopeful candidate, the complicated FaSTAR program is difficult to pick up time consuming cores and implement them on an FPGA. In practical aircraft design, a parametric survey, which executes FaSTAR jobs in parallel with different conditions is commonly used. Here, we propose a Zynq cluster as a cost and power efficient solution of FaSTAR parametric survey. By introducing high-level synthesis and partial reconfiguration, the FaSTAR job with a specific condition runs on a simple node with a Zynq-7000 AP SoC. Now a part of FaSTAR job can be executed on FPGA of Zynq board about 1.3 times faster than Intel’s Xeon E5-2667 2.9GHz software.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages287-299
Number of pages13
Volume9625
ISBN (Print)9783319304809
DOIs
Publication statusPublished - 2016
Event12th International Symposium on Applied Reconfigurable Computing, ARC 2016 - Mangaratiba, Brazil
Duration: 2016 Mar 222016 Mar 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9625
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Symposium on Applied Reconfigurable Computing, ARC 2016
CountryBrazil
CityMangaratiba
Period16/3/2216/3/24

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Sugimoto, N., Miyajima, T., Sakai, R., Osana, Y., Fujita, N., & Amano, H. (2016). Zynq cluster for CFD parametric survey. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9625, pp. 287-299). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9625). Springer Verlag. https://doi.org/10.1007/978-3-319-30481-6_23