Task Parallelism in the WRF Model Through Computation Offloading to Many-Core Devices

Rodrigo Baya, C. Porrini, M. Pedemonte, P. Ezzatti
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引用次数: 2

Abstract

In the last decade the use of hybrid hardware (e.g., multicore processors + coprocessors) has been growing on the HPC field. However, this evolution in the HPC hardware has not been fully exploited by the WRF model since it shows limitations in the scalability when a large number of computing units are used. In a previous work, we proposed an asynchronous architecture for the WRF that overlaps the radiation computation with the execution of the rest of the model. In this work, we extend this idea with the aim of exploiting the computational power offered by hybrid hardware platforms. Specifically, we implement an OpenMP version of the asynchronous architecture and include the use of two types of coprocessors, a Xeon Phi and a GPU. The experimental evaluation performed shows that our proposal is able to adequately exploit these secondary computation devices, reaching interesting runtime reductions when solving tests cases from real scenarios.
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WRF模型中多核设备计算卸载的任务并行性
在过去十年中,混合硬件(例如,多核处理器+协处理器)在高性能计算领域的使用一直在增长。然而,WRF模型并没有充分利用HPC硬件的这种演变,因为当使用大量计算单元时,它显示出可伸缩性的局限性。在之前的工作中,我们为WRF提出了一种异步架构,该架构将辐射计算与模型其余部分的执行重叠。在这项工作中,我们扩展了这个想法,目的是利用混合硬件平台提供的计算能力。具体来说,我们实现了一个OpenMP版本的异步架构,包括使用两种类型的协处理器,Xeon Phi和GPU。实验评估表明,我们的建议能够充分利用这些辅助计算设备,在从真实场景中解决测试用例时达到有趣的运行时间减少。
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