期刊
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 17, 期 4, 页码 2034-2053出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.0c01164
关键词
-
资金
- European Research Council (ERC) under the European Union [810367]
- GENCI (France)
- NVIDIA
- French state funds by the CalSimLab LABEX
- ANR within the Investissements d'Avenir program [ANR11-IDEX-0004-02]
- Direction Generale de l'Armement (DGA) Maitrise NRBC of the French Ministry of Defense
- GENCI on the Jean Zay machine (IDRIS) [A0070707671]
- National Institutes of Health [R01GM106137, R01GM114237]
- HPE
The Tinker-HP package has been extended to use GPU cards for accelerated molecular dynamics simulations, offering high-performance modules with multiple precision capabilities. Various NVIDIA platforms have been tested to provide performance benchmarks for large biosystems, significantly reducing solution times.
We present the extension of the Tinker-HP package (Lagarde're, 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 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).
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据