工作站
计算机科学
计算流体力学
并行计算
星团(航天器)
计算机集群
计算科学
计算
库达
超级计算机
操作系统
航空航天工程
算法
工程类
作者
Bastien Di Pierro,Sarah Hank
标识
DOI:10.1016/j.compfluid.2024.106187
摘要
This paper examines the parallel efficiency of an ARM-based single board computing cluster made of 16 Raspberry Pi 4 and 8 Nvidia Jetson Nano Single Board Computer, considering both CPU and GPU parallel implementation of CFD applications. It is found that the parallelization scales up to 16 Raspberry Pi 4 and 8 Nvidia Jetson Nano (maximum available on the current cluster). Moreover, it is shown that regarding the computation time, about 12 SBC are as fast as a classical computing workstation. Finally, it is shown that such cluster are energy efficient considering CFD applications.
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