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OpenACC acceleration for the P_N-P_(N-2) algorithm in Nek5000

机译:Nek5000中P_N-P_(N-2)算法的OpenACC加速

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Due to its high performance and throughput capabilities, GPU-accelerated computing is becoming a popular technology in scientific computing, in particular using programming models such as CUDA and OpenACC. The main advantage with OpenACC is that it enables to simply port codes in their "original" form to GPU systems through compiler directives, thus allowing an incremental approach. An OpenACC implementation is applied to the CFD code Nek5000 for simulation of incompressible flows, based on the spectral-element method. The work follows up previous implementations and focuses now on the P-N-PN-2 method for the spatial discretization of the Navier-Stokes equations. Performance results of the ported code show a speed-up of up to 3.1 on multi-GPU for a polynomial order N 11. (C) 2019 Elsevier Inc. All rights reserved.
机译:由于其高性能和吞吐能力,GPU加速计算正成为科学计算中的一种流行技术,尤其是使用诸如CUDA和OpenACC之类的编程模型时。 OpenACC的主要优点在于,它可以通过编译器指令简单地将其“原始”形式的代码移植到GPU系统,从而允许采用增量方法。基于频谱元素方法,将OpenACC实现应用于CFD代码Nek5000,以模拟不可压缩的流。这项工作是在先前的实现之后进行的,现在集中在用于Navier-Stokes方程的空间离散化的P-N-PN-2方法上。移植的代码的性能结果显示,对于N> 11的多项式,多GPU上的加速高达3.1。(C)2019 Elsevier Inc.保留所有权利。

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