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Communication efficient work distributions in stencil operation based applications

机译:基于模板操作的应用程序中的通信有效工作分配

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摘要

In recent years, the use of accelerators in conjunction with CPUs, known as heterogeneous computing, hasrnbrought about significant performance increases for scientific applications. One of the best examples ofrnthis is lattice quantum chromodynamics (QCD), a stencil operation based simulation. These simulationsrnhave a large memory footprint necessitating the use of many graphics processing units (GPUs) in parallel.rnThis requires the use of a heterogeneous cluster with one or more GPUs per node. In order to obtainrnoptimal performance, it is necessary to determine an efficient communication pattern between GPUs onrnthe same node and between nodes. In this paper, we present a performance model based method for minimizingrnthe communication time of applications with stencil operations, such as lattice QCD, on heterogeneousrncomputing systems with a non-blocking InfiniBand interconnection network. The proposedrnmethod is able to increase the performance of the most computationally intensive kernel of lattice QCDrnby 25% due to improved overlapping of communication and computation. We also demonstrate that thernaforementioned performance model and efficient communication patterns can be used to determine a costrnefficient heterogeneous system design for stencil operation based applications.
机译:近年来,将加速器与CPU结合使用(称为异构计算)已为科学应用带来了显着的性能提升。最好的例子之一是晶格量子色动力学(QCD),一种基于模版操作的模拟。这些模拟具有较大的内存占用量,因此需要并行使用许多图形处理单元(GPU)。这需要使用每个节点具有一个或多个GPU的异构集群。为了获得最佳性能,有必要确定同一节点上的GPU之间以及节点之间的有效通信模式。在本文中,我们提出了一种基于性能模型的方法,该方法可以在具有无阻塞InfiniBand互连网络的异构计算系统上,将带有模板操作(例如点阵QCD)的应用程序的通信时间最小化。由于改进了通信和计算的重叠,所提出的方法能够将计算密集度最高的晶格QCDrn的性能提高25%。我们还演示了上述性能模型和有效的通信模式可用于确定基于模板操作的应用程序的高性价比异构系统设计。

著录项

  • 来源
    《Concurrency and Computation》 |2015年第13期|3262–3280|共1页
  • 作者单位

    Department of Electrical and Computer Engineering, The George Washington University, Washington, DC, USA;

    Department of Electrical and Computer Engineering, The George Washington University, Washington, DC, USACE IT4Innovations, VSB-Technical University of Ostrava, Czech Republic;

    Department of Electrical and Computer Engineering, The George Washington University, Washington, DC, USA;

    Department of Electrical and Computer Engineering, The George Washington University, Washington, DC, USA;

    Department of Physics, The George Washington University, Washington, DC, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    heterogeneous computing; GPU acceleration; performance model; stencil operation; nearest neighbor;

    机译:异构计算GPU加速;绩效模型;模板操作;最近的邻居;

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