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首页> 外文期刊>Journal of chemical theory and computation: JCTC >Efficient, Regularized, and Scalable Algorithms for Multiscale Coarse-Graining
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Efficient, Regularized, and Scalable Algorithms for Multiscale Coarse-Graining

机译:高效,正则化和可扩展的多尺度粗粒度算法

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摘要

the multiscale coarse-graining (MS-CG) method obtains CG interactions from atomistic configurations, as demonstrated previously for a variety of soft matter and biological systems. In this article, recent advances in MS-CG algorithms are described, and a recently developed computer program MSCGFM for MS-CG calculations is introduced. The algorithms enhance the efficiency and stability of MS-CG computations, and these algorithms are incorporated into the MSCGFM program. As a result of these efforts, MS-CG calculations on large scale systems such as peptide and proteins can become tractable, and the numerical stability of solutions for ill-posed MS-CG problems can be regularized efficiently. Various parallelization strategies are also discussed.
机译:多尺度粗粒度(MS-CG)方法从原子构型获得CG相互作用,如先前针对各种软物质和生物系统所证明的。本文介绍了MS-CG算法的最新进展,并介绍了最近开发的用于MS-CG计算的计算机程序MSCGFM。该算法提高了MS-CG计算的效率和稳定性,并且这些算法已合并到MSCGFM程序中。这些努力的结果是,可以在诸如肽和蛋白质之类的大规模系统上进行MS-CG计算,并且可以有效地规范不适定MS-CG问题的解的数值稳定性。还讨论了各种并行化策略。

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