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Evaluation of the 3-D finite difference implementation of the acoustic diffusion equation model on massively parallel architectures

机译:大规模并行架构中声扩散方程模型的3-D有限差分实现的评估

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The diffusion equation model is a popular tool in room acoustics modeling. The 3-D Finite Difference (3D-FD) implementation predicts the energy decay function and the sound pressure level in closed environments. This simulation is computationally expensive, as it depends on the resolution used to model the room. With such high computational requirements, a high-level programming language (e.g., Matlab) cannot deal with real life scenario simulations. Thus, it becomes mandatory to use our computational resources more efficiently. Manycore architectures, such as NVIDIA GPUs or Intel Xeon Phi offer new opportunities to enhance scientific computations, increasing the performance per watt, but shifting to a different programming model. This paper shows the roadmap to use massively parallel architectures in a 3D-FD simulation. We evaluate the latest generation of NVIDIA and Intel architectures. Our experimental results reveal that NVIDIA architectures outperform by a wide margin the Intel Xeon Phi co-processor while dissipating approximately 50W less (25%) for large-scale input problems. (C) 2015 Elsevier Ltd. All rights reserved.
机译:扩散方程模型是室内声学建模中的一种流行工具。 3-D有限差分(3D-FD)实现可预测封闭环境中的能量衰减函数和声压级。这种模拟的计算量很大,因为它取决于用于对房间建模的分辨率。在如此高的计算要求下,高级编程语言(例如Matlab)无法处理现实生活中的场景模拟。因此,必须更有效地使用我们的计算资源。诸如NVIDIA GPU或Intel Xeon Phi之类的许多核心架构为增强科学计算能力,提高每瓦性能提供了新的机会,但是却转向了不同的编程模型。本文展示了在3D-FD仿真中使用大规模并行架构的路线图。我们评估最新一代的NVIDIA和Intel架构。我们的实验结果表明,NVIDIA架构在性能上远胜过Intel Xeon Phi协处理器,同时在大规模输入问题上的功耗降低了约50W(25%)。 (C)2015 Elsevier Ltd.保留所有权利。

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