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Comparison of parallel computing approaches of a finite-difference implementation of the acoustic diffusion equation model

机译:声扩散方程模型有限差分实现的并行计算方法比较

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The diffusion equation model has been intensively researched as a room-acoustics simulation algorithm during last years. A 3-D finite-difference implementation of this model was proposed to evaluate the propagation over time of sound field within rooms. Despite the computational saving of this model to calculate the room energy impulse response, elapsed times are still long when high spatial resolutions and/or simulations in several frequency bands are needed. In this work, several data-parallel approaches of this finite-difference solution on Graphics Processing Units are proposed using a compute unified device architecture programming model. A comparison of their performance running on different models of Nvidia GPUs is carried out. In general, 2D vertical block approach running in a Tesla K20C shows the best speed-up of more than 15 times versus CPU version.
机译:近年来,作为房间声学模拟算法,对扩散方程模型进行了深入研究。提出了该模型的3-D有限差分实现,以评估房间内声场随时间的传播。尽管该模型在计算上节省了计算房间能量脉冲响应的能力,但是当需要在几个频带上进行高空间分辨率和/或仿真时,经过的时间仍然很长。在这项工作中,使用计算统一设备体系结构编程模型,提出了图形处理单元上这种有限差分解决方案的几种数据并行方法。比较了它们在不同型号的Nvidia GPU上运行的性能。通常,在Tesla K20C中运行的2D垂直块方法显示出的最佳加速比CPU版本高15倍以上。

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