Classical molecular dynamics (MD) calculations represent a significant part of the utilization time of high-performance computing systems. As usual, the efficiency of such calculations is based on an interplay of software and hardware that are nowadays moving to hybrid GPU-based technologies. Several well-developed open-source MD codes focused on GPUs differ both in their data management capabilities and in performance. In this work, we analyze the performance of LAMMPS, GROMACS and OpenMM MD packages with different GPU backends on Nvidia Volta and AMD Vega20 GPUs. We consider the efficiency of solving two identical MD models (generic for material science and biomolecular studies) using different software and hardware combinations. We describe our experience in porting the CUDA backend of LAMMPS to ROCm HIP that shows considerable benefits for AMD GPUs comparatively to the OpenCL backend.

经典的分子动力学（MD）计算代表了高性能计算系统使用时间的重要部分。像往常一样，这种计算的效率是基于当今正在转向基于混合GPU的技术的软件和硬件的相互作用。几个专注于GPU的开发良好的开源MD代码在数据管理功能和性能上都不同。在这项工作中，我们分析了Nvidia Volta和AMD Vega20 GPU上具有不同GPU后端的LAMMPS，GROMACS和OpenMM MD软件包的性能。我们考虑使用不同的软件和硬件组合来求解两个相同的MD模型（材料科学和生物分子研究通用）的效率。