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Discrete event performance prediction of speculatively parallel temperature-accelerated dynamics

机译:推测性并行温度加速动力学的离散事件性能预测

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Due to its unrivaled ability to predict the dynamical evolution of interacting atoms, molecular dynamics (MD) is a widely used computational method in theoretical chemistry, physics, biology, and engineering. Despite its success, MD is only capable of modeling timescales within several orders of magnitude of thermal vibrations, leaving out many important phenomena that occur at slower rates. The temperature-accelerated dynamics (TAD) method overcomes this limitation by thermally accelerating the state-to-state evolution captured by MD. Due to the algorithmically complex nature of the serial TAD procedure, implementations have yet to improve performance by parallelizing the concurrent exploration of multiple states. Here we utilize a discrete-event-based application simulator to introduce and explore a new speculatively parallel TAD (SpecTAD) method. We investigate the SpecTAD algorithm, without a full-scale implementation, by constructing an application simulator proxy (SpecTADSim). Following this method, we discover that a non-trivial relationship exists between the optimal SpecTAD parameter set and the number of CPU cores available at run-time. Furthermore, we find that a majority of the available SpecTAD boost can be achieved within an existing TAD application using relatively simple algorithm modifications.
机译:由于其无与伦比的预测相互作用原子动力学演化的能力,分子动力学(MD)是理论化学,物理学,生物学和工程学中广泛使用的计算方法。尽管取得了成功,但MD仅能够在几个数量级的热振动中对时间尺度进行建模,而忽略了许多以较慢的速率发生的重要现象。温度加速动力学(TAD)方法通过热加速MD捕获的状态到状态演化来克服此限制。由于串行TAD过程的算法复杂性,实现方式尚未通过并行化多个状态的并发探索来提高性能。在这里,我们利用基于离散事件的应用程序模拟器来介绍和探索一种新的推测性并行TAD(SpecTAD)方法。我们通过构建应用程序模拟器代理(SpecTADSim),研究了没有全面实现的SpecTAD算法。遵循这种方法,我们发现最佳SpecTAD参数集与运行时可用的CPU内核数量之间存在不平凡的关系。此外,我们发现,使用相对简单的算法修改,就可以在现有TAD应用程序中实现大多数可用的SpecTAD增强。

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