TY - GEN
T1 - Zynq cluster for CFD parametric survey
AU - Sugimoto, Naru
AU - Miyajima, Takaaki
AU - Sakai, Ryotaro
AU - Osana, Yasunori
AU - Fujita, Naoyuki
AU - Amano, Hideharu
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-319-30481-6_23
DO - 10.1007/978-3-319-30481-6_23
M3 - Conference contribution
AN - SCOPUS:84961248738
SN - 9783319304809
VL - 9625
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 287
EP - 299
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer Verlag
T2 - 12th International Symposium on Applied Reconfigurable Computing, ARC 2016
Y2 - 22 March 2016 through 24 March 2016
ER -