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Large-scale ferrofluid simulations on graphics processing units

机译:图形处理单元上的大规模铁磁流体模拟

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摘要

We present an approach to molecular-dynamics simulations of ferrofluids on graphics processing units (GPUs). Our numerical scheme is based on a GPU-oriented modification of the Barnes-Hut (BH) algorithm designed to increase the parallelism of computations. For an ensemble consisting of a million ferromagnetic particles, the performance of the proposed algorithm on a Tesla M2050 GPU demonstrated a computational-time speed-up of four orders of magnitude compared to the performance of the sequential All-Pairs (AP) algorithm on a single-core CPU, and two orders of magnitude compared to the performance of the optimized AP algorithm on the GPU. The accuracy of the scheme is corroborated by comparing the results of numerical simulations with theoretical predictions.
机译:我们提出了一种在图形处理单元(GPU)上对铁磁流体进行分子动力学模拟的方法。我们的数值方案基于Barnes-Hut(BH)算法的面向GPU的修改,旨在提高计算的并行性。对于由一百万个铁磁粒子组成的集合,与在机器上的顺序全对(AP)算法的性能相比,在Tesla M2050 GPU上提出的算法的性能证明了四个数量级的计算时间加速。单核CPU,与GPU上优化的AP算法相比,性能提高了两个数量级。通过将数值模拟的结果与理论预测相比较,可以证实该方案的准确性。

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