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Performance analysis of single-phase, multiphase,and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

机译:GPU集群上单相,多相和多组分晶格-玻尔兹曼流体流动性能分析

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The lattice-Boltzmann method is well suited for implementation in single-instruction multiple-data (SIMD) environments provided by general purpose graphics processing units (GPGPUs). This paper discusses the integration of these GPGPU programs with OpenMP to create lattice-Boltzmann applications for multi-GPU clusters. In addition to the standard single-phase single-component lattice-Boltzmann method, the performances of more complex multiphase, multicomponent models are also examined. The contributions of various GPU lattice-Boltzmann parameters to the performance are examined and quantified with a statistical model of the performance using Analysis of Variance (ANOVA). By examining single- and multi-GPU lattice-Boltzmann simulations with ANOVA, we show that all the lattice-Boltzmann simulations primarily depend on effects corresponding to simulation geometry and decomposition, and not on the architectural aspects of GPU. Additionally, using ANOVA we confirm that the metrics of Efficiency and Utilization are not suitable for memory-bandwidth-dependent codes.
机译:格子-波尔兹曼方法非常适合在通用图形处理单元(GPGPU)提供的单指令多数据(SIMD)环境中实现。本文讨论了这些GPGPU程序与OpenMP的集成,以为多GPU集群创建点阵-玻尔兹曼应用程序。除了标准的单相单组分晶格-玻尔兹曼方法外,还检查了更复杂的多相,多组分模型的性能。使用方差分析(ANOVA),使用性能统计模型检查并量化各种GPU晶格-玻尔兹曼参数对性能的贡献。通过使用ANOVA检查单GPU和多GPU格子-玻尔兹曼仿真,我们发现所有格子-玻尔兹曼仿真主要取决于与仿真几何和分解相对应的效果,而不取决于GPU的体系结构方面。此外,使用方差分析,我们确认效率和利用率的度量标准不适用于与存储器带宽相关的代码。

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