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Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

机译:用于现代GPU,CPU和MIC架构的多维蒙特卡洛集成的矢量化算法

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The aim of this paper is to show that the multidimensional Monte Carlo integration can be efficiently implemented on computers with modern multicore CPUs and manycore accelerators including Intel MIC and GPU architectures using a new vectorized version of LCG pseudorandom number generator which requires limited amount of memory. We introduce two new implementations of the algorithm based on directive-based parallel programming standards OpenMP and OpenACC and consider their performance using Hockney-Jesshope theoretical model of vector computations. We also present and discuss the results of experiments performed on dual-processor Intel Xeon E5-2670 computers with Intel Xeon Phi 7120P and NVIDIA K40m.
机译:本文的目的是说明使用新型矢量化版本的LCG伪随机数生成器需要有限的内存量,可以在具有现代多核CPU和包括Intel MIC和GPU架构在内的许多核加速器的计算机上有效地实现多维蒙特卡洛集成。我们基于基于指令的并行编程标准OpenMP和OpenACC引入了该算法的两个新实现,并使用Hockney-Jesshope矢量计算理论模型来考虑其性能。我们还将介绍并讨论在装有Intel Xeon Phi 7120P和NVIDIA K40m的双处理器Intel Xeon E5-2670计算机上进行的实验结果。

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