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Tinker-HP:使用 GPU 和多 GPU 系统加速具有高级点偶极可极化力场的大型复杂系统的分子动力学模拟。

Tinker-HP: Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields Using GPUs and Multi-GPU Systems.

机构信息

Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France.

Sorbonne Université, IP2CT, FR2622 CNRS, F-75005 Paris, France.

出版信息

J Chem Theory Comput. 2021 Apr 13;17(4):2034-2053. doi: 10.1021/acs.jctc.0c01164. Epub 2021 Mar 23.

Abstract

We present the extension of the Tinker-HP package (Lagardère, 2018, 9, 956-972) to the use of Graphics Processing Unit (GPU) cards to accelerate molecular dynamics simulations using polarizable many-body force fields. The new high-performance module allows for an efficient use of single- and multiple-GPU architectures ranging from research laboratories to modern supercomputer centers. After detailing an analysis of our general scalable strategy that relies on OpenACC and CUDA, we discuss the various capabilities of the package. Among them, the multiprecision possibilities of the code are discussed. If an efficient double precision implementation is provided to preserve the possibility of fast reference computations, we show that a lower precision arithmetic is preferred providing a similar accuracy for molecular dynamics while exhibiting superior performances. As Tinker-HP is mainly dedicated to accelerate simulations using new generation point dipole polarizable force field, we focus our study on the implementation of the AMOEBA model. Testing various NVIDIA platforms including 2080Ti, 3090, V100, and A100 cards, we provide illustrative benchmarks of the code for single- and multicards simulations on large biosystems encompassing up to millions of atoms. The new code strongly reduces time to solution and offers the best performances to date obtained using the AMOEBA polarizable force field. Perspectives toward the strong-scaling performance of our multinode massive parallelization strategy, unsupervised adaptive sampling and large scale applicability of the Tinker-HP code in biophysics are discussed. The present software has been released in phase advance on GitHub in link with the High Performance Computing community COVID-19 research efforts and is free for Academics (see https://github.com/TinkerTools/tinker-hp).

摘要

我们展示了 Tinker-HP 包(Lagardère,2018,9,956-972)的扩展,将其用于图形处理单元(GPU)卡,以加速使用极化多体力场的分子动力学模拟。新的高性能模块允许在从研究实验室到现代超级计算中心的单 GPU 和多 GPU 架构中高效使用。在详细分析了我们依赖 OpenACC 和 CUDA 的可扩展策略之后,我们讨论了该包的各种功能。其中,讨论了代码的多精度可能性。如果提供高效的双精度实现以保留快速参考计算的可能性,我们将展示较低精度的算法更优,因为它在提供类似分子动力学精度的同时表现出更高的性能。由于 Tinker-HP 主要致力于加速使用新一代点偶极极化力场的模拟,我们专注于 AMOEBA 模型的实现。我们在各种 NVIDIA 平台上进行了测试,包括 2080Ti、3090、V100 和 A100 卡,提供了单卡和多卡模拟的代码基准测试,涵盖了多达数百万个原子的大型生物系统。新代码大大缩短了求解时间,并提供了迄今为止使用 AMOEBA 极化力场获得的最佳性能。讨论了我们的多节点大规模并行化策略的强扩展性、无监督自适应采样以及 Tinker-HP 代码在生物物理学中的大规模适用性的前景。该软件已在 GitHub 上提前发布,与高性能计算社区 COVID-19 研究工作相关联,对学术界免费(请参见 https://github.com/TinkerTools/tinker-hp)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31c1/8047816/17b9b68e240b/ct0c01164_0004.jpg

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