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Performance of SOR methods on modern vector and scalar processors

机译:SOR方法在现代矢量和标量处理器上的性能

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The building-cube method (BCM) is a new generation algorithm for CFD simulations. The basic idea of BCM is to simplify the algorithm in all stages of flow computation to achieve large-scale simulations. Calculation of a pressure field using the Successive Over Relaxation (SOR) method consumes most of the total execution time required for BCM. In this paper, effective implementations on modern vector and scalar processors are investigated. NEC SX-9 and Intel Nehalem-EX are the latest vector and scalar processors. Those processors have much higher peak performances than their previous-generation processors. However, their memory bandwidth improvement cannot catch up with the performance improvement of processors. This is the so-called memory wall problem. In our paper, we discuss optimization techniques for implementation of the SOR method based on architectural characteristics of these modern processors, and evaluate their effects on the sustained performances of these processors for BCM.
机译:建筑立方体方法(BCM)是用于CFD仿真的新一代算法。 BCM的基本思想是简化流计算各个阶段的算法,以实现大规模仿真。使用连续过度松弛(SOR)方法计算压力场会消耗BCM所需的总执行时间的大部分。本文研究了在现代矢量和标量处理器上的有效实现。 NEC SX-9和Intel Nehalem-EX是最新的矢量和标量处理器。这些处理器的峰值性能比上一代处理器高得多。但是,它们的内存带宽提高无法赶上处理器性能的提高。这就是所谓的内存墙问题。在本文中,我们讨论了基于这些现代处理器的体系结构特征实现SOR方法的优化技术,并评估了它们对BCM这些处理器的持续性能的影响。

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