Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer

Porting Adaptive Ensemble Molecular Dynamics Workflows to the Summit Supercomputer
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将自适应集成分子动力学工作流程移植到 Summit 超级计算机

DOI:
10.1007/978-3-030-34356-9_30
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发表时间:
2019
期刊:
Proceedings International Conference on High Performance Computing
影响因子:
--
通讯作者:
John Ossyra, Ada Sedova
John Ossyra, Ada Sedova
中科院分区:
--
文献类型:
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作者:
John Ossyra, Ada Sedova

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分子动力学(MD)模拟必须在模拟时间内采取非常小的(飞秒)积分步骤,以避免数值误差。在最先进的MD程序中,并行编程模型和加速器的有效使用现在正在推动摩尔的每MD步骤的时间限制。因此,直接模拟毫秒以上的时间尺度将无法直接实现,即使是在艾级。然而,来自统计物理学的概念可以用于联合收割机许多并行模拟,以提供关于更长时间尺度的信息,并对模拟空间进行充分采样,同时保留关于系统动态的细节。实施这种方法需要一个工作流程程序,允许根据对中间结果的广泛统计分析来适应性地指导任务分配。在这里,我们报告这样一个适应性强的工作流程程序,以推动模拟的首脑会议IBM电力系统AC922,一个前exascale超级计算机在橡树岭领导计算设施(OLCF)。我们比较泰坦,首脑会议的前身,报告的工作流程及其组件的性能,并描述移植过程中的经验。我们发现,使用由Mongo数据库管理的工作流程序可以提供容错性,可扩展的性能,任务调度率和可重构性所需的鲁棒性和便携式实施的合奏模拟,如用于增强采样分子动力学。这种类型的工作流生成器还可以用于为除了MD之外的其他应用提供系综模拟的自适应转向。
Molecular dynamics (MD) simulations must take very small (femtosecond) integration steps in simulation-time to avoid numerical errors. Efficient use of parallel programming models and accelerators in state-of-the art MD programs now is pushing Moore’s limit for time-per-MD step. As a result, directly simulating timescales beyond milliseconds will not be attainable directly, even at exascale. However, concepts from statistical physics can be used to combine many parallel simulations to provide information about longer timescales and to adequately sample the simulation space, while preserving details about the dynamics of the system. Implementing such an approach requires a workflow program that allows adaptable steering of task assignments based on extensive statistical analysis of intermediate results. Here we report the implementation of such an adaptable workflow program to drive simulations on the Summit IBM Power System AC922, a pre-exascale supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). We compare to experiences on Titan, Summit’s predecessor, report the performance of the workflow and its components, and describe the porting process. We find that using a workflow program managed by a Mongo database can provide the fault tolerance, scalable performance, task dispatch rate, and reconfigurability required for robust and portable implementation of ensemble simulations such as are used in enhanced-sampling molecular dynamics. This type of workflow generator can also be used to provide adaptive steering of ensemble simulations for other applications in addition to MD.
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