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Hybrid parallelization of a multi-tree path search algorithm: Application to highly-flexible biomolecules

机译:多树路径搜索算法的混合并行化:在高度灵活的生物分子中的应用

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摘要

The study of the conformational energy landscape of a molecule is essential for the understanding of its physicochemical properties. This requires the exploration of a continuous, high-dimensional space to identify the most probable conformations and the transition paths between them. The problem is computationally difficult, in particular for highly-flexible biomolecules such as Intrinsically Disordered Proteins (IDPs). In recent years, a robotics-inspired algorithm called Transition-based Rapidly-exploring Random Tree (TRRT) has been proposed to solve this problem, and has been shown to provide good results with small and middle-sized biomolecules. Aiming to treat larger systems, we propose a hybrid strategy for the efficient parallelization of a multi-tree variant of TRRT, called Multi-TRRT, enabling an efficient execution in (possibly large) computer clusters. The parallel algorithm uses OpenMP multi-threading for computation inside each multi-core processor and MPI to perform the communication between processors. Results show a near-linear speedup for a wide range of cluster configurations. Although the paper mainly deals with the application of the proposed parallel algorithm to the investigation of biomolecules, the explanations concerning the methods are general, aiming to inspire future work on the parallelization of related algorithms.
机译:研究分子的构象能图对于理解其理化性质至关重要。这需要探索一个连续的高维空间,以识别最可能的构象及其之间的过渡路径。该问题在计算上是困难的,特别是对于高度柔性的生物分子,例如固有紊乱蛋白(IDP)。近年来,已经提出了一种基于机器人的算法,称为基于过渡的快速探索随机树(TRRT),可以解决该问题,并且已证明在中小型生物分子方面可提供良好的结果。为了处理较大的系统,我们提出了一种混合策略,用于有效并行化称为Multi-TRRT的TRRT的多树变量,从而可以在(可能是大型的)计算机集群中高效执行。并行算法使用OpenMP多线程在每个多核处理器中进行计算,并使用MPI执行处理器之间的通信。结果表明,在各种群集配置下,其线性加速程度都很高。尽管本文主要讨论了所提出的并行算法在生物分子研究中的应用,但有关方法的解释是通用的,目的是启发有关算法并行化的未来工作。

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