FPGA-Based Scalable Custom Computing Accelerator for Computational Fluid Dynamics Based on Lattice BoltzmannMethod

Kentaro Sano ()
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Kentaro Sano: Tohoku University, Graduate School of Information Sciences

A chapter in Sustained Simulation Performance 2014, 2015, pp 187-201 from Springer

Abstract: Abstract This paper presents a tightly-coupled FPGA cluster for custom computing of fluid dynamics simulation, and evaluates its performance with prototype implementation. For scalable and efficient computation with a lot of FPGA accelerators, we propose an accelerator-domain network (ADN) that brings low-latency and high-speed data transfer by directly connecting FPGAs. We describe implementation of a prototype cluster node with four FPGAs, and their on-chip framework for high-speed data streaming and computing. In performance evaluation, we demonstrate that our custom computing machine for fluid dynamics computation with the lattice-Boltzmann method (LBM) exploits both temporal and spatial parallelism, and scales the performance well with the number of FPGAs. As a result, we achieved 98.8 % of the peak performance of 73.0 GFlop/s with four FPGAs.

Keywords: Tightly-coupled FPGA cluster; Custom computing; Lattice Boltzmann method; Accelerator domain network (ADN) (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-10626-7_16

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DOI: 10.1007/978-3-319-10626-7_16

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