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Accelerating modified Shepard interpolated potential energy calculations using graphics processing units

机译:使用图形处理单元加速修改后的Shepard插值势能计算

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The potential energy surfaces constructed with the modified Shepard interpolation scheme have been widely used in studies of chemical reaction dynamics. However, computational costs of interpolation increase rapidly with the size of the system and the number of data points needed to achieve a given accuracy. In this work, we present a naive Graphics Processing Unit (GPU)-accelerated algorithm for modified Shepard interpolated potential energy calculations and its implementation with the PGI CUDA Fortran language. The benchmark tests on a NVIDIA Tesla C2050 using four interpolated potential energy surfaces (one for H+H_2O?H_2+OH, two for H+NH _3?H_2+NH_2 and one for H+CH _4?H_2+CH_3) demonstrated a speedup of 50-fold over the original CPU implementation on an Intel E5620 processor and the speedup increases with the system size and the number of data points. This work presents a promising GPU application in the field of chemical reaction dynamics.
机译:用改进的Shepard插值方案构造的势能面已广泛用于化学反应动力学的研究。但是,插值的计算成本随着系统的大小和达到给定精度所需的数据点数量而迅速增加。在这项工作中,我们提出了一种朴素的图形处理单元(GPU)加速算法,用于修改的Shepard插值势能计算及其在PGI CUDA Fortran语言中的实现。在NVIDIA Tesla C2050上进行的基准测试使用了四个内插势能面(一个用于H + H_2O?H_2 + OH,两个用于H + NH _3?H_2 + NH_2,一个用于H + CH _4?H_2 + CH_3)证明了加速与Intel E5620处理器上的原始CPU实施相比提高了50倍,并且速度随着系统大小和数据点数量的增加而增加。这项工作提出了在化学反应动力学领域中有希望的GPU应用。

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