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Tinker-HP:利用GPU和多GPU系统,通过先进的点偶极可极化力场加速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-GPUs systems.

作者信息

Adjoua Olivier, Lagardère Louis, Jolly Luc-Henri, Durocher Arnaud, Very Thibaut, Dupays Isabelle, Wang Zhi, Inizan Théo Jaffrelot, Célerse Frédéric, Ren Pengyu, Ponder Jay W, Piquemal Jean-Philip

出版信息

ArXiv. 2021 Mar 3:arXiv:2011.01207v4.

PMID:33173801
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7654869/
Abstract

We present the extension of the Tinker-HP package (Lagard`ere et al., Chem. Sci., 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 multi-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 multi-precision 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 multi-cards 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 multi-node 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

我们展示了对Tinker-HP软件包(Lagardère等人,《化学科学》,2018年,9卷,956 - 972页)的扩展,使其能够使用图形处理单元(GPU)卡,以利用可极化多体势场加速分子动力学模拟。这个新的高性能模块允许在从研究实验室到现代超级计算机中心的各种单GPU和多GPU架构上高效使用。在详细分析了我们基于OpenACC和CUDA的通用可扩展策略之后,我们讨论了该软件包的各种功能。其中,讨论了代码的多精度可能性。如果提供了高效的双精度实现以保留快速参考计算的可能性,我们表明较低精度的算法更受青睐,因为它在分子动力学中能提供相似的精度,同时表现出卓越的性能。由于Tinker-HP主要致力于使用新一代点偶极可极化势场加速模拟,我们将研究重点放在AMOEBA模型的实现上。通过测试各种NVIDIA平台,包括2080Ti、3090、V100和A100卡,我们为包含多达数百万个原子的大型生物系统的单卡和多卡模拟提供了代码的说明性基准测试。新代码大大减少了求解时间,并提供了迄今为止使用AMOEBA可极化势场获得的最佳性能。我们还讨论了多节点大规模并行化策略的强缩放性能、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。本软件已提前在GitHub上发布,与高性能计算社区的COVID-19研究工作相关联,并且对学术界免费(见https://github.com/TinkerTools/tinker-hp)。