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OpenACC Parallelisation for Diffusion Problems, Applied to Temperature Distribution on a Honeycomb Around the Bee Brood: A Worked Example Using BiCGSTAB

机译:用于扩散问题的OpenACC并行性,应用于蜂窝周围蜂窝状的温度分布:使用BicGstab的一个工作示例

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We discuss a simple OpenACC implementation of the iterative BiCGSTAB algorithm for linear systems. Problems of this type arise in the numerical solution of diffusion-reaction problems, where the linear solver constitutes the most computationally expensive component of the simulation (~80% of time spent) and therefore has often been the primary target for parallelization. We deploy and test this method on a desktop workstation with two supported GPUs, one targeted for high performance computing, one a consumer level GPU, to compute the temperature distribution on a honeycomb around the bee brood. The paper is written from a user's, not from a GPU computing expert's perspective and aims to fill a gap we noticed between real world application problems and the simple problems solved in introductory OpenACC tutorials or in benchmarking studies.
机译:我们讨论了用于线性系统迭代BICGSTAB算法的简单OpenACC实现。这种类型的问题在扩散反应问题的数值解中出现,其中线性求解器构成了模拟的最昂贵的昂贵组件(〜80%的时间),因此通常是并行化的主要目标。我们在具有两个支持的GPU的桌面工作站上部署和测试此方法,其中一个针对高性能计算,一个消费级GPU,用于计算蜂巢周围蜂窝上的温度分布。本文是由用户编写的,而不是来自GPU计算专家的观点,旨在填补我们在现实世界应用问题之间注意到的差距,并在介绍的OpenACC教程中或基准研究中解决了简单的问题。

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