Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures
Institute of Mathematics, Maria Curie-Sklodowska University, Pl. Marii Curie-Sklodowskiej 1, 20-031 Lublin, Poland
The Journal of Supercomputing, 2017
@article{stpiczynski2017vectorized,
title={Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures},
author={Stpiczy{‘n}ski, Przemys{l}aw},
journal={The Journal of Supercomputing},
pages={1–17},
publisher={Springer},
year={2017}
}
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.
November 12, 2017 by hgpu
