并行和可扩展的定制计算实时流体模拟上的集群节点与四个紧密耦合的fpga

K. Sano, R. Ito, Hayato Suzuki, Yoshiaki Kono
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引用次数: 0

摘要

只提供摘要形式。基于计算流体动力学(CFD)的数值模拟现在是一种不可或缺的技术,特别是在工业中,因为它能够以比使用风洞的实验更低的成本获取各种数据。晶格玻尔兹曼方法(LBM)是一种用于计算多相流等各种问题的CFD方法。LBM具有良好的并行性,但同时计算每个点阵点需要大量数据,导致运算强度较低。因此,当使用通用处理器和gpu计算时,LBM的持续性能受到内存带宽而不是算术性能的限制。更糟糕的是,互连网络的带宽不足和高延迟导致并行计算的开销相对较大,特别是在强扩展的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel and scalable custom computing for real-time fluid simulation on a cluster node with four tightly-coupled FPGAs
Summary form only given. Numerical simulation based on computational fluid dynamics (CFD) is now an indispensable technique especially in industry due to its acquisition capability of various data at a lower cost than experiments using a wind tunnel. The lattice Boltzmann method (LBM) is one of the CFD schemes, which is used to compute various problems including multiphase flow. LBM has good parallelism, but simultaneously requires many data to compute each lattice point, resulting in a low operational intensity. Consequently, the sustained performance of LBM is limited by memory bandwidth rather than arithmetic performance when computed by using general-purpose processors and GPUs. To make matters worse, insufficient bandwidth and high-latency of an interconnection network cause a relatively big overhead in parallel computing, especially in the case of strong-scaling.
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