Molecular dynamics simulations with many-body potentials on multiple GPUs-The implementation, package and performance

Molecular dynamics simulations with many-body potentials on multiple GPUs-The implementation, package and performance
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多 GPU 上的多体势分子动力学模拟 - 实现、封装和性能

DOI:
10.1016/j.cpc.2013.03.026
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发表时间:
2013-09-01
影响因子:
6.3
通讯作者:
Wang, Jun
Wang, Jun
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Hou, Qing;Li, Min;Wang, Jun

文献摘要

被引文献

相似文献

分子动力学是材料科学中广泛应用的重要研究工具。在图形处理单元(GPU)上运行MD是一种有吸引力的加速MD模拟的新方法。目前,MD的GPU实现通常运行在单主机处理单GPU(OHPOG)方案中。由于设备内存相对于主机内存较小,该方案可能会对实现方式可以处理的系统大小造成限制。在本文中,我们提出了一个单主机处理器多GPU(OHPMG)实现的MD嵌入原子模型或半经验紧束缚多体势。因为在OHPMG进程中有更多的设备内存可用,所以可以处理的系统大小增加到几百万或更多个原子。与采用牛顿第三定律提高计算效率的串行CPU实现相比,OHPMG实现在双精度下实现了28.9x-86.0x的加速比,这取决于系统大小、截止范围和GPU数量。该实现还可以通过将小盒子组合成大盒子来在一次运行中处理一组小模拟盒子。这种方法大大提高了GPU的计算效率时,需要大量的MD模拟的小盒子的统计目的。(C)2013爱思唯尔有限公司版权所有。
Molecular dynamics (MD) is an important research tool extensively applied in materials science. Running MD on a graphics processing unit (GPU) is an attractive new approach for accelerating MD simulations. Currently, GPU implementations of MD usually run in a one-host-process-one-GPU (OHPOG) scheme. This scheme may pose a limitation on the system size that an implementation can handle due to the small device memory relative to the host memory. In this paper, we present a one-host-process-multiple-GPU (OHPMG) implementation of MD with embedded-atom-model or semi-empirical tight-binding many-body potentials. Because more device memory is available in an OHPMG process, the system size that can be handled is increased to a few million or more atoms. In comparison with the serial CPU implementation, in which Newton's third law is applied to improve the computational efficiency, our OHPMG implementation has achieved a 28.9x-86.0x speedup in double precision, depending on the system size, the cut-off ranges and the number of GPUs. The implementation can also handle a group of small simulation boxes in one run by combining the small boxes into a large box. This approach greatly improves the GPU computing efficiency when a large number of MD simulations for small boxes are needed for statistical purposes. (C) 2013 Elsevier B.V. All rights reserved.