GromEx: Highly Scalable Unified Long-Range Electrostatics and Flexible Ionization for Realistic Biomolecular Simulations on the Exascale

GromEx：高度可扩展的统一远程静电和灵活电离，可实现百亿亿级真实生物分子模拟

• 批准号: 230673686
• 负责人: Dr. Holger Dachsel
• 金额: --
• 依托单位: Department of Theoretical Physics
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2015-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/230673686?language=en
• 关键词: GromEx; Highly; Scalable; Unified; Long

Computer simulations on the basis of theoretical physics and chemistry have grown to be invaluable tools of scientific research on molecular function and structure. Such simulations share common challenges with simulations on other strongly interacting systems, e.g. in astrophysics. Advancing the field of molecular simulation to exascale computing is thus highly beneficial to science and the public. The most costly part of molecular simulations is the computation of electrostatic long-range interactions. Thus, the efficiency of calculating these interactions is decisive for the whole simulation. Molecular electrostatics is complicated by the fact that molecules can contain titratable sites whose charge distribution varies over time. This variability originates, e.g., from protonation or redox reactions, or binding of different drug molecules. These reactions are intricately coupled to electrostatics as well as crucial for the function and interaction properties of many (bio)molecules. Thus, a realistic treatment of electrostatics in biomolecular simulation has to account for the different forms of titratable sites. The particle mesh Ewald method (PME, currently state of the art in molecular simulation) does not scale to large core counts as it suffers from a communication bottleneck, and does not treat titratable sites efficiently. In this project, we combine a fast multipole method (FMM) with a lambda-dynamics method to both alleviate the PME bottleneck and, for the first time, enable realistic chemical variability of titratable sites in molecular simulations. The FMM will enable an efficient calculation of long-range interactions on massively parallel exascale computers, including alternative charge distributions representing various forms of titratable sites. lambda-dynamics allows for a smooth interconversion between site forms during the simulation which is indispensable for efficient, fully atomistic molecular simulations. In the second funding period, we aim to open up a whole new application range for molecular simulation, both in terms of the hardware that can be utilized at optimum performance and in terms of the type of scientific problems that can be addressed. In detail we will: 1. Extend the current code to allow for multiple local topologies of each site. This will let simulations account for the whole range of variability of titratable sites instead of just protonation 2. Enable our solver to take full advantage of future exascale hardware including many-core CPUs and accelerators like GPUs or Xeon Phi coprocessors 3. For optimum scaling on this heterogeneous hardware, we will design and implement a graph- based partitioning scheme to choose from algorithmic alternatives according to latency and throughput of the available hardware devices Example applications include computational drug design and simulations on the function of nanomachines.

以理论物理和化学为基础的计算机模拟已成为分子功能和结构科学研究的宝贵工具。这种模拟与其他强相互作用系统（例如天体物理学）的模拟有共同的挑战。因此，将分子模拟领域推进到艾级计算对科学和公众都非常有益。分子模拟中最昂贵的部分是静电长程相互作用的计算。因此，计算这些相互作用的效率对于整个模拟是决定性的。分子静电学是复杂的事实，分子可以包含可滴定的网站，其电荷分布随时间而变化。这种可变性起源于，例如，来自质子化或氧化还原反应，或不同药物分子的结合。这些反应与静电学错综复杂地结合在一起，对许多（生物）分子的功能和相互作用性质至关重要。因此，在生物分子模拟中，静电学的现实处理必须考虑不同形式的可滴定位点。粒子网格埃瓦尔德方法（PME，目前最先进的分子模拟）不能扩展到大的核心计数，因为它遭受通信瓶颈，并没有有效地处理可滴定的网站。在这个项目中，我们结合联合收割机的快速多极方法（FMM）与一个非线性动力学方法，既减轻PME瓶颈，并首次，使现实的化学可变性的可滴定的网站在分子模拟。FMM将使大规模并行exascale计算机上的远程相互作用的有效计算，包括替代电荷分布代表各种形式的可滴定的网站。双动力学允许在模拟过程中站点形式之间的平滑相互转换，这对于高效的、完全原子化的分子模拟是不可或缺的。在第二个资助期内，我们的目标是为分子模拟开辟一个全新的应用范围，无论是在可以以最佳性能使用的硬件方面，还是在可以解决的科学问题类型方面。具体来说，我们将：1.扩展当前代码，以允许每个站点的多个本地拓扑。这将使模拟考虑可滴定位点的整个可变性范围，而不仅仅是质子化2。使我们的求解器能够充分利用未来的兆兆级硬件，包括众核CPU和GPU或Xeon Phi协处理器等加速器3。为了在这种异构硬件上进行最佳缩放，我们将设计和实现基于图的分区方案，以根据可用硬件设备的延迟和吞吐量从算法替代方案中进行选择。示例应用包括计算药物设计和纳米机器功能的模拟。