首页> 外文期刊>Parallel Computing >Full-neighbor-list based numerical reproducibility method for parallel molecular dynamics simulations
【24h】

Full-neighbor-list based numerical reproducibility method for parallel molecular dynamics simulations

机译:基于全邻居列表的数值可再现性方法用于并行分子动力学模拟

获取原文
获取原文并翻译 | 示例

摘要

The numerical nonreproducibility in parallel molecular dynamics (MD) simulations, which relates to the non-associate accumulation of float point data, leads to great challenges for development, debugging and validation. The most common solutions to this problem are using a high-precision data type or operation sorting, but these solutions are accompanied by significant computational overhead. This paper analyzes the sources of nonreproducibility in parallel MD simulations in detail. Two general solutions, namely, sorting by force component value and using an 80-bit long double data type, are implemented and evaluated in LAMMPS. To optimize the computational cost, a full-list based method with operation order sorted by particle distance is proposed, which is inspired by the spatial characteristics of MD simulations. An experiment on a system with constant energy dynamics shows that the new method can ensure reproducibility at any parallelism with an extra 50% computational overhead. (C) 2019 Published by Elsevier B.V.
机译:并行分子动力学(MD)模拟中的数值不可重现性与浮点数据的非相关累积有关,这给开发,调试和验证带来了巨大挑战。此问题的最常见解决方案是使用高精度数据类型或操作排序,但是这些解决方案伴随着大量的计算开销。本文详细分析了并行MD模拟中不可再现性的来源。在LAMMPS中实现并评估了两个通用解决方案,即按力分量值排序和使用80位长的double数据类型。为了优化计算成本,提出了一种基于全列表的,按粒子距离对操作顺序进行排序的方法,该方法受MD模拟的空间特性的启发。在具有恒定能量动力学的系统上进行的实验表明,该新方法可以确保在任何并行度下都具有可重现性,且额外的计算开销为50%。 (C)2019由Elsevier B.V.发布

著录项

  • 来源
    《Parallel Computing》 |2019年第7期|109-118|共10页
  • 作者单位

    Natl Univ Def Technol, State Key Lab High Performance Comp, Changsha, Hunan, Peoples R China;

    Natl Innovat Inst Def Technol, Artificial Intelligence Res Ctr, Beijing, Peoples R China;

    Natl Univ Def Technol, State Key Lab High Performance Comp, Changsha, Hunan, Peoples R China;

    Natl Innovat Inst Def Technol, Artificial Intelligence Res Ctr, Beijing, Peoples R China;

    Natl Univ Def Technol, State Key Lab High Performance Comp, Changsha, Hunan, Peoples R China|Natl Innovat Inst Def Technol, Beijing, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Molecular dynamics; Numerical reproducibility; Parallel programming; LAMMPS; Floating-Point arithmetic;

    机译:分子动力学;数值再现性;并行编程;LAMMPS;浮点算法;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号