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本文引用的文献

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2
GENESIS 1.1: A hybrid-parallel molecular dynamics simulator with enhanced sampling algorithms on multiple computational platforms.《创世纪1.1》:一款在多个计算平台上具有增强采样算法的混合并行分子动力学模拟器。
J Comput Chem. 2017 Sep 30;38(25):2193-2206. doi: 10.1002/jcc.24874. Epub 2017 Jul 18.
3
Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm.生物分子相互作用在细菌细胞质的原子模型中调节大分子的结构和动力学。
Elife. 2016 Nov 1;5:e19274. doi: 10.7554/eLife.19274.
4
Graphics Processing Unit Acceleration and Parallelization of GENESIS for Large-Scale Molecular Dynamics Simulations.用于大规模分子动力学模拟的GENESIS的图形处理单元加速与并行化
J Chem Theory Comput. 2016 Oct 11;12(10):4947-4958. doi: 10.1021/acs.jctc.6b00241. Epub 2016 Sep 27.
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Mesoscale Modeling Reveals Hierarchical Looping of Chromatin Fibers Near Gene Regulatory Elements.中尺度建模揭示基因调控元件附近染色质纤维的分层环状结构
J Phys Chem B. 2016 Aug 25;120(33):8642-53. doi: 10.1021/acs.jpcb.6b03197. Epub 2016 Jun 16.
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Wiley Interdiscip Rev Comput Mol Sci. 2015 Jul;5(4):310-323. doi: 10.1002/wcms.1220. Epub 2015 May 7.
7
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CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data.CHARMM36 全原子加和蛋白力场:基于 NMR 数据比较的验证。
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大规模生物物理模拟中超越 10 万处理器核心的分子动力学扩展。

Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations.

机构信息

Computational Biophysics Research Team, RIKEN Center for Computational Science, Kobe 650-0047, Japan.

Los Alamos National Laboratory, Los Alamos, New Mexico.

出版信息

J Comput Chem. 2019 Aug 5;40(21):1919-1930. doi: 10.1002/jcc.25840. Epub 2019 Apr 17.

DOI:10.1002/jcc.25840
PMID:30994934
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7153361/
Abstract

The growing interest in the complexity of biological interactions is continuously driving the need to increase system size in biophysical simulations, requiring not only powerful and advanced hardware but adaptable software that can accommodate a large number of atoms interacting through complex forcefields. To address this, we developed and implemented strategies in the GENESIS molecular dynamics package designed for large numbers of processors. Long-range electrostatic interactions were parallelized by minimizing the number of processes involved in communication. A novel algorithm was implemented for nonbonded interactions to increase single instruction multiple data (SIMD) performance, reducing memory usage for ultra large systems. Memory usage for neighbor searches in real-space nonbonded interactions was reduced by approximately 80%, leading to significant speedup. Using experimental data describing physical 3D chromatin interactions, we constructed the first atomistic model of an entire gene locus (GATA4). Taken together, these developments enabled the first billion-atom simulation of an intact biomolecular complex, achieving scaling to 65,000 processes (130,000 processor cores) with 1 ns/day performance. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.

摘要

对生物相互作用复杂性的日益关注不断推动着生物物理模拟中系统规模的扩大,这不仅需要强大先进的硬件,还需要能够适应大量通过复杂力场相互作用的原子的适应性软件。为了解决这个问题,我们在 GENESIS 分子动力学包中开发并实现了针对大量处理器的策略。通过最小化涉及通信的进程数量,对长程静电相互作用进行了并行化处理。我们实现了一种新的非键相互作用算法,以提高单指令多数据 (SIMD) 的性能,从而减少超大规模系统的内存使用。通过使用描述物理 3D 染色质相互作用的实验数据,我们构建了整个 GATA4 基因座的第一个原子模型。总之,这些发展使我们能够对完整的生物分子复合物进行第一次十亿原子的模拟,实现了扩展到 65000 个进程(130000 个处理器核)、1ns/day 性能的模拟。2019 年发表。本文是美国政府的一项工作,在美国属于公有领域。

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