NeuDATool:一个开源的中子数据分析工具,支持GPU硬件加速,以及跨计算机集群节点并行

Changli Ma, He Cheng, Taisen Zuo, Guisheng Jiao, Zehua Han
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引用次数: 2

摘要

经验势结构精化(EPSR)是一种中子散射数据分析算法和软件包。它是由英国散裂中子源(ISIS)无序材料小组于20世纪80年代开发的,旨在构建无序液体最可能的原子结构。在过去的几十年里,它被广泛使用,并产生了可靠的结果。然而,它是用Fortran编程的,并使用OpenMP实现了共享内存架构。随着超级计算机集群的广泛构建和图形处理单元(GPU)加速技术的广泛使用,现在有必要利用这些技术对EPSR进行重建,以提高其计算速度。本文提出了一个开源框架NeuDATool。它是用面向对象语言c++编写的,可以在计算机集群内的节点之间并行,并支持GPU加速。用水和非晶硅中子散射数据对NeuDATool的性能进行了测试。测试结果表明,该软件能够正确地重建样品的微观结构,在大约10万个原子的模拟盒中,与CPU串行算法相比,GPU加速的计算速度提高了400倍以上。NeuDATool为熟悉c++编程并希望为其分析定义特定模型和算法的科学家提供了另一种选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NeuDATool: An open source neutron data analysis tools, supporting GPU hardware acceleration, and across-computer cluster nodes parallel
Empirical potential structure refinement (EPSR) is a neutron scattering data analysis algorithm and a software package. It was developed by the British spallation neutron source (ISIS) Disordered Materials Group in 1980s, and aims to construct the most-probable atomic structures of disordered liquids. It has been extensively used during the past decades, and has generated reliable results. However, it is programmed in Fortran and implements a shared-memory architecture with OpenMP. With the extensive construction of supercomputer clusters and the widespread use of graphics processing unit (GPU) acceleration technology, it is now necessary to rebuild the EPSR with these techniques in the effort to improve its calculation speed. In this study, an open source framework NeuDATool is proposed. It is programmed in the object-oriented language C++, can be paralleled across nodes within a computer cluster, and supports GPU acceleration. The performance of NeuDATool has been tested with water and amorphous silica neutron scattering data. The test shows that the software could reconstruct the correct microstructure of the samples, and the calculation speed with GPU acceleration could increase by more than 400 times compared with CPU serial algorithm at a simulation box consists about 100 thousand atoms. NeuDATool provides another choice for scientists who are familiar with C++ programming and want to define specific models and algorithms for their analyses.
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