论文标题
Tinker-HP:使用GPU和Multi-GPUS System
Tinker-HP : Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems
论文作者
论文摘要
我们介绍了Tinker-HP软件包(Lagardère等人,Chem。Sci。,2018,9,956-972)的扩展,以使用图形处理单元(GPU)卡来加速使用可极化的多体力场加速分子动力学模拟。新的高性能模块允许有效利用从研究实验室到现代超级计算机中心等单GPU体系结构。在详细介绍了依赖OpenACC和CUDA的一般可扩展策略的分析之后,我们讨论了包装的各种功能。其中,讨论了代码的多个过度可能性。如果提供了有效的双精度实现来保留快速参考计算的可能性,我们表明,优选较低的精度算术是优选的,在表现出卓越的性能的同时,为分子动力学提供了相似的精度。由于Tinker-HP主要致力于使用New Generation Point偶极极化力场加速模拟,因此我们将研究重点放在Amoeba模型的实现上。在测试各种NVIDIA平台,包括2080TI,3090,V100和A100卡,我们为大型生物系统的单牌模拟代码提供了说明性的基准,这些基准包括多达数百万个原子的大型生物系统。新代码大大减少了解决方案的时间,并提供了迄今使用Amoeba Extalizable Force场获得的最佳性能。讨论了我们多节点大规模并行化策略,无监督的自适应抽样和生物物理学中Tinker-HP代码的大规模适用性的观点。本软件已与高性能计算社区COVID-19研究工作链接在GitHub上的阶段发布中,并且对于学者免费(请参阅https://github.com/tinkertools/tinker-hp)。
We present the extension of the Tinker-HP package (Lagardère 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).